Optical Characterization of Coastal Waters with Atmospheric Correction Errors: Insights from SGLI and AERONET-OC by Hiroto Higa, Masataka Muto, Salem Ibrahim Salem, Hiroshi Kobayashi, Joji Ishizaka, Kazunori Ogata, Mitsuhiro Toratani, Kuniaki Takahashi, Fabrice Maupin, Stephane Victori

“…Furthermore, relatively high light absorption by phytoplankton and colored dissolved organic matter, plus non-algal particles, was confirmed in these regions. This occurs because atmospheric correction processing excessively subtracts aerosol light scattering due to the influence of aerosol absorption, increasing the probability of the occurrence of negative <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><msub><mrow><mi>L</mi></mrow><mrow><mi>w</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> values. …”
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Generating synthetic as-built additive manufacturing surface topography using progressive growing generative adversarial networks by Junhyeon Seo, Prahalada Rao, Bart Raeymaekers

“…Abstract Numerically generating synthetic surface topography that closely resembles the features and characteristics of experimental surface topography measurements reduces the need to perform these intricate and costly measurements. However, existing algorithms to numerically generated surface topography are not well-suited to create the specific characteristics and geometric features of as-built surfaces that result from laser powder bed fusion (LPBF), such as partially melted metal particles, porosity, laser scan lines, and balling. …”
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Runtime Scheduling, Allocation, and Execution of Real-Time Hardware Tasks onto Xilinx FPGAs Subject to Fault Occurrence by Xabier Iturbe, Khaled Benkrid, Chuan Hong, Ali Ebrahim, Tughrul Arslan, Imanol Martinez

“…These algorithms consider most of the technological constraints existing in modern partially reconfigurable FPGAs as well as spontaneously occurring faults and emerging permanent damage in the silicon substrate of the chip. …”
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METHODOLOGY AND RESULTS OF THE MAIN TECHNICAL OF PARAMETERS OF THE MANEUVERABLE UNMANNED AERIAL VEHICLE JUSTIFICATION by M. A. Kiselev

“…The greatest challenge lies in creating the algorithms, data sensors, control hardware, communications hardware, etc. necessary for utilization of an unmanned aerial vehicle (UAV). …”
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Study of methods for extracting contours of objects on raster images of amber samples by Yu.O. Podchashynskyi, A.V. Ryzhuk

“…TVS can determine fine particles, various inclusions, cracks, and texture on the examined surface much better, using various methods and algorithms for contour detection and further processing of the obtained results. …”
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Optimization of Traffic Flow by Allowing Private Cars to Merge into the Bus Lane at Specific Locations by Zhentao Yin, Kai Yuan, Shenshen Zheng

“…We use the genetic algorithms to optimize the system. Finally, simulation results show that the partially space-shared bus lane reduces private-car delays and total delays of the system. …”
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Integrating microplastic research in sustainable agriculture: Challenges and future directions for food production by Marcelo Illanes, María-Trinidad Toro, Mauricio Schoebitz, Nelson Zapata, Diego A. Moreno, María Dolores López-Belchí

“…., pharmaceuticals, plastic particles, or pesticides), combined with environmental conditions, remains understudied. …”
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From Physically Based to Generative Models: A Survey on Underwater Image Synthesis Techniques by Lucas Amparo Barbosa, Antonio Lopes Apolinario

“…Given the complexity of capturing data from the sea and the large variability of environmental components (depth, distance, suspended particles, turbidity, etc.), synthesized underwater scenes can provide relevant data to improve image processing algorithms and computer vision tasks. …”
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Acoustic modelling of machines by Z. ENGEL, L. STRYCZNIEWICZ

“…Mathematical dependencies, algorithms of modelling and examples of calculation results are included in the paper.…”
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A spiking neural network model of model-free reinforcement learning with high-dimensional sensory input and perceptual ambiguity. by Takashi Nakano, Makoto Otsuka, Junichiro Yoshimoto, Kenji Doya

“…This class of problem is formally known as partially observable reinforcement learning (PORL) problems. …”
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Enhancing Autonomous Driving in Urban Scenarios: A Hybrid Approach with Reinforcement Learning and Classical Control by Rodrigo Gutiérrez-Moreno, Rafael Barea, Elena López-Guillén, Felipe Arango, Fabio Sánchez-García, Luis M. Bergasa

“…Specifically, the authors address the Decision Making problem by employing a Partially Observable Markov Decision Process formulation and offer a solution through the use of Deep Reinforcement Learning algorithms. …”
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Bayesian Prediction Intervals Based on Type-I Hybrid Censored Data from the Lomax Distribution under Step-Stress Model by Abdalla Rabie, Abd EL-Baset A. Ahmad, Mohamad A. Fawzy, Tahani A. Aloafi

“…The observed data is censored using a Type-I hybrid censoring scheme under a step-stress partially accelerated life test. There are two types of sampling schemes considered: one-sample and two-sample. …”
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Recursive GNNs for Learning Precoding Policies With Size-Generalizability by Jia Guo, Chenyang Yang

“…These merits are important for learning wireless policies under dynamic environments, which partially come from the matched permutation equivariance (PE) properties of the GNNs to the policies to be learned. …”
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Monte Carlo modeling of multileaf collimators using the code Geant4 by Alex Cristóvão Holanda de Oliveira, José Wilson Vieira, Fernando Roberto Andrade Lima

“…The equipment most often used in radiotherapy to the patient irradiation is linear accelerator (Linac). Among the many algorithms developed for evaluation of dose distributions in radiotherapy planning, the algorithms based on Monte Carlo (MC) methods have proven to be very promising in terms of accuracy by providing more realistic results. …”
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Parallel art:artistic creation under human-machine collaboration by Chao GUO, Yue LU, Yilun LIN, Fan ZHUO, Fei-Yue WANG

“…The artistic creation of machine has drawn considerable attention and achieved significant development in recent years.There are more and more artworks processed partially by specific algorithms,or even created entirely by machines.Despite their popularity,it is hard for these artworks to be accepted by humans because of their underwhelming sensory impacts and lack of empathy.However,their impact is highly concerned by the art community.A theoretical framework called the parallel art system was proposed to solve the technical and human-machine-relationship challenges in artistic creation.The system aims to build a partnership between humans and machines,enabling them to collaborate in a parallel manner,and even provide a new way to integrate human emotion and machine logic.…”
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Advancements in Retinal Tissue-Mimicking Optical Coherence Tomography Phantoms: Materials, Properties, and Applications by Mukhit Kulmaganbetov

“…Optical coherence tomography (OCT) phantoms are essential tools for calibrating imaging systems, validating diagnostic algorithms, and bridging technological advancements with clinical applications. …”
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Microphysical detection of nano-ice nuclei to ice crystals: a platform for ice nucleation research by Devendra Pal, Ryan Hall, Yevgen Nazarenko, Leonard Barrie, Parisa A. Ariya

“…This platform enables real-time detection and differentiation of ice crystals and supercooled droplets, providing microphysical information into their spherical or non-spherical morphology, surface roughness, and phase characteristics, particularly for ice particles smaller than 500 nm. Automated algorithms facilitate the differentiation of individual and aggregated ice crystals within a size range of 390 nm to 100 µm, supporting time-resolved analyses of ice nucleation processes. …”
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Clinical decision support for vestibular diagnosis: large-scale machine learning with lived experience coaching by Cecilia A. Callejas Pastor, Hyun Tae Ryu, Jung Sook Joo, Yunseo Ku, Myung-Whan Suh

“…The model incorporates 50 clinical features, selected through a hybrid approach combining algorithmic methods (RFE-SVM and SKB score) and expert clinical knowledge. …”
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Enhancing prediction of fluid-saturated fracture characteristics using deep learning super resolution by Manju Pharkavi Murugesu, Vignesh Krishnan, Anthony R. Kovscek

“…While past literature has offered solutions to improve resolution of CT rock images, including deep learning-based algorithms, our study uniquely focuses on improving dynamic, partially and fully fluid-saturated geological images. …”
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Research Advances in Large Deformation Analysis and Applications of the Material Point Method by Changhong Zhou, Qing Zhong, Xuejiao Zhou, Xionghua Wu, Shiyi Chen

“…This paper begins by introducing the fundamental theory and contact algorithms of the MPM. It then systematically summarizes the latest advancements and applications of the MPM, including its hybridization and coupling with other algorithms, in simulating various large deformation scenarios such as high-speed impacts, explosions, dynamic cracking, penetration, and fluid–structure interactions. …”
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