Observations of Optical Properties and Chlorophyll-a Concentration in Qiandao Lake Using Shipborne Lidar by Xuan Sang, Zhihua Mao, Youzhi Li, Xianliang Zhang, Chang Han, Longwei Zhang, Haiqing Huang

“…However, these models cannot be directly applied to inland waters due to their complex composition, and research on the biological parameters and optical properties of inland waters remains limited. …”
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Advances in Surveying Topographically Complex Ecosystems with UAVs: Manta Ray Foraging Algorithms by Shijie Yang, Jiateng Yuan, Zhibo Chen, Hanchao Zhang, Xiaohui Cui

“…Comparative experimental results on real terrain data and MATLAB r2018b simulation show that the error between the corrected energy calculation equation and the actual value is controlled within 5%, and the accuracy is improved by 10% over the original equation. …”
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Optimization and Benchmarking of Image Segmentation for Improved Landmark Detection in Lower Limb X-Rays and Accurate Coronal Plane Alignment of the Knee Classification by Sebastian Amador Sanchez, Ashkan Zarghami, Philippe van Overschelde, Jef Vandemeulebroucke

“…The evaluation assessed the landmark detection error and phenotype classification accuracy based on lower limb alignment. …”
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Deep Learning Spinal Cord Segmentation Based on B0 Reference for Diffusion Tensor Imaging Analysis in Cervical Spondylotic Myelopathy by Shuoheng Yang, Ningbo Fei, Junpeng Li, Guangsheng Li, Yong Hu

“…However, the segmentation of spinal cord DTI images primarily relies on manual methods, which are labor-intensive and heavily dependent on the subjective experience of clinicians, and existing research on DTI automatic segmentation cannot fully satisfy clinical requirements. …”
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LightSTATE: A Generalized Framework for Real-Time Human Activity Detection Using Edge-Based Video Processing and Vision Language Models by Anik Debnath, Yong-Woon Kim, Yung-Cheol Byun

“…The system processes video streams through efficient frame extraction, edge detection and Root Mean Square Error (RMSE)-based frame filtering to identify significant motion events. …”
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A supervised machine learning statistical design of experiment approach to modeling the barriers to effective snakebite treatment in Ghana. by Eric Nyarko, Edmund Fosu Agyemang, Ebenezer Kwesi Ameho, Louis Agyekum, José María Gutiérrez, Eduardo Alberto Fernandez

“…However, significant challenges in achieving this goal include a lack of robust research evidence related to snakebite incidence and treatment, particularly in sub-Saharan Africa. …”
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Aligning Evapotranspiration from MOD16A2.061 Product to Ground Estimates in Piemonte (NW Italy): an analysis of temporal and spatial biases by E. Ronco, E. C. Borgogno Mondino

“…The corrected dataset (<em>&Ecirc;T</em>₀) shows significantly improved agreement with ground-based ET₀, reducing the Mean Absolute Error from 10.06 mm/8 d to 2.48 mm/8 d, a 75% improvement. …”
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Validation of Enzyme Immunoassay for Preclinical Pharmacokinetic Trials of Rituximab by V. V Pisarev, Maria M Ulyashova, Gelia N Gildeeva

“…An integral part of preclinical pharmacokinetic studies is the development of a bioanalytical method for determination of the drug in a biological fluid.The aim of the research was to assess the suitability of the test system based on enzyme-linked immunosorbent assay (ELISA) for quantitative determination of rituximab in the blood serum of laboratory animals after intravenous administration of rituximab at a dose corresponding to the therapeutic dose in humans. …”
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Takagi–Sugeno Fuzzy Nonlinear Control System for Optical Interferometry by Murilo Franco Coradini, Luiz Henrique Vitti Felão, Stephany de Souza Lyra, Marcelo Carvalho Minhoto Teixeira, Claudio Kitano

“…This method has been applied in various fields of scientific research: buck converters, biomedicine, civil engineering, etc. …”
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Translation and Validation of the Premenstrual Assessment Form-Short Form Questionnaire in Hungarian by Olívia Dózsa-Juhász, Alexandra Makai, Viktória Prémusz, Pongrác Ács, Márta Hock

“…Introduction: Premenstrual symptoms, including premenstrual syndrome and its more severe form premenstrual dysphoric disorder, are a set of somatic and psychological symptoms that occur during the luteal phase of the menstrual cycle. Our research aimed to adapt the Hungarian version of the Premenstrual Assessment Form-Short Form (PAF-SF), a questionnaire suitable for assessing premenstrual symptoms, and to examine its reliability, validity, and applicability. …”
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PlantGaussian: Exploring 3D Gaussian splatting for cross-time, cross-scene, and realistic 3D plant visualization and beyond by Peng Shen, Xueyao Jing, Wenzhe Deng, Hanyue Jia, Tingting Wu

“…As a generic 3D digital plant model, PlantGaussian will support expansion of plant phenotype databases, ecological research, and remote expert consultations.…”
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5G New Radio for Non-Terrestrial Networks: Analysis and Comparison of HARQ and RLC ARQ Performance Over Satellite Links by Riccardo Tuninato, Gabriel Maiolini Capez, Nicolo Mazzali, Roberto Garello

“…Finally, we provide a detailed comparison and discussion of HARQ and RLC ARQ performance in terms of block error rate, spectral efficiency, and latency. This extensive analysis provides valuable insights for researchers and space agencies interested in applying 5G NR to satellite-based Non-Terrestrial Networks.…”
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Retrieval of Chinese fir tree parameters under different understory conditions with the integration of handheld and airborne Lidar data by Yunhe Li, Guiying Li, Sirong Wang, Dengsheng Lu

“…Results showed that (1) tree DBHs were accurately extracted with relative root mean square error (RMSEr) of 7.1%−10.5% and stem volume with an RMSEr of 12.3%−16.8% under different understory conditions; (2) As stand structure became complex, direct extraction of tree DBHs from HLS data became a challenging task. …”
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A neural network-based model for cultivating applied talents in the context of industry-education integration by Lei Tong, Jingjing Zhang, Lixiao Yue, Li Chen, Mengxiang Wang

“…PBL and Flipped Classroom were more effective in fostering innovation and academic research skills. This study contributes to the optimization of teaching evaluation models and provides insights into improving education through neural networks. …”
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Melt Density Monitoring of Extruder Extrusion Process Based on Multi-source Data Fusion and Convolutional Long Short-term Memory Neural Network by Binbin ZHANG, Zhuyun CHEN, Fei ZHANG, Gang JIN

“…Ensuring precise control over melt density is imperative for achieving desired product characteristics and maintaining process stability in polymer blending operations.Methods The research proposes a novel methodological framework that integrates multi-source data fusion with a convolutional long short-term memory (LSTM) neural network architecture to address this challenge. …”
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Exploring the impact of noise, language familiarity, and experimental settings on emotion recognition by Terry Amorese, Marialucia Cuciniello, Anna Alterio, Daniele Pepe, Odette Scharenborg, Gennaro Cordasco, Anna Esposito

“…Regarding familiarity with the language, differences in emotion recognition performance between the Italian and Dutch listeners were observed, but the error magnitude was contingent on the emotional categories. …”
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Edge-optimized multimodal cross-fusion architecture for efficient crop disease detection by Thomas Kinyanjui Njoroge, Kelvin Mugoye Shindu, Rachael Kibuku

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Quality of life and unmet needs in patients with fabry disease: a qualitative study by Montserrat Morales, Jordi Cruz, Eduardo Brignani, Laura Acuña, Esther Lázaro, Cristina Soria

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Wavelet Multiresolution Analysis-Based Takagi–Sugeno–Kang Model, with a Projection Step and Surrogate Feature Selection for Spectral Wave Height Prediction by Panagiotis Korkidis, Anastasios Dounis

“…The proposed methodology is applied to a real-world time series pertaining to spectral wave height and obtained from the Poseidon operational oceanography system at the Institute of Oceanography, part of the Hellenic Center for Marine Research. Numerical studies showcase a high degree of approximation performance. …”
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MONITORING DATA AGGREGATION OF DYNAMIC SYSTEMS USING INFORMATION TECHNOLOGIES by Dmytro Shevchenko, Mykhaylo Ugryumov, Sergii Artiukh

“…The following tasks were solved: analysis of existing dimensionality reduction approaches, description of the general architecture of vanilla and variational autoencoders, development of their architecture, development of software for training and testing of autoencoders, conducting research on the performance quality of autoencoders for the problem of dimensionality reduction. …”
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