Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…This study integrates deep learning networks with existing image processing techniques to enable more precise and comprehensive identification of suspended sediment particles. …”
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Scientometric analysis of computational calculations on hydrogen adsorption by D.A. Torres-Ceron, S. Amaya-Roncancio, F. Fuentes-Gandara, E. Restrepo-Parra, L. Bohorquez-Santiago, J.P. Velasquez-Tamayo

“…The retrieved data were analysed with the Bibliometrix package in RStudio to evaluate publication trends, research evolution across three distinct periods and global collaboration networks. …”
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Context-Specific Impact Of Antimicrobial Stewardship On Antibiotic Use And Antibiotic Resistance In Hospitals In A Lower-Middle Income Country - Results From Implementation Study W... by Trang Quynh Le, Dung Tien Viet Vu, Quang Minh Le, Huyen Thi Thu Nguyen, Vinh Hai Vu, Duc Minh Chau, Em Thi Hoang Dung Vo, Tu Thi Cam Nguyen, Quan Anh Truong, Khanh Hong Nguyen, Hoa Nguyen Minh Le, Thomas Kesteman, Elizabeth Dodds Ashley, Deverick J. Anderson, Hugo C. Turner, Thach Ngoc Pham, Ben S. Cooper, Choisy Marc, H Rogier Van Doorn, Huong Thi Lan Vu

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Use of camera traps to record wild red panda activity in eastern Nepal by Sonam T. Lama, Kathryn A. Bugler, James G. Ross, Adrian M. Paterson

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Urban fluxes for free: Estimating urban turbulent surface fluxes from crowdsourced meteorological canyon layer observations by W. van der Meer, F. Zantinge, G.J. Steeneveld

“…Also, the spatial variance of temperatures recorded in a network of Netatmo stations (varT) appears to be a good predictor for the incoming solar radiation. …”
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SMaRT: Stick via Motion and Recognition Tracker by Fatih Emre Simsek, Cevahir Cigla, Koray Kayabol

“…This integration enables the simultaneous regression of object locations and extraction of re-identification vectors within a single neural network. Evaluations on the DIVOTrack, MOT17 and SOMPT22 datasets demonstrate significant improvements over previous state-of-the-art methods in terms of Higher Order Tracking Accuracy (HOTA), Multi-Object Tracking Accuracy (MOTA), and Association Accuracy (AssA). …”
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An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning by L. Ravi Kumar, Ravi Kumar Tata, T. R. Mahesh, Endris Mohammed Ali

“…Deep learning is used to analyze the image patterns and to recognize the objects. The detection process includes the creation of labels with bounding boxes, and it will be evaluated by using accuracy scores. …”
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Impact of the COVID-19 pandemic on incident diagnoses in German refugee centres 2018 to 2023 by Kayvan Bozorgmehr, Stella Erdmann, Sven Rohleder, Consortium Pri.CareNet, Rosa Jahn

“…Here, we employ segmented regression analyses, adjusting for time trends, socio-demographic factors, occupancy, and centre characteristics, to evaluate the COVID-19 pandemic’s impact on incident diagnosis patterns among refugees. …”
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Group attention for collaborative filtering with sequential feedback and context aware attributes by Hadise Vaghari, Mehdi Hosseinzadeh Aghdam, Hojjat Emami

“…However, due to individual variations in rating patterns and dynamic interplays of item attributes, it becomes challenging to model user preferences accurately. …”
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Interactive online learning method for students based on artificial intelligence by Cizhang Li, Wenfen Yin

“…This study proposes a novel approach that integrates the Dwarf Mongoose Optimization (DMO) algorithm with a Gated Recurrent Unit (GRU) neural network to develop an AI-powered interactive online learning model. …”
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Transforming physical fitness and exercise behaviors in adolescent health using a life log sharing model by Shanshan Wang, Jingwu Liu

“…IntroductionThis study investigates the potential of a deep learning-based Life Log Sharing Model (LLSM) to enhance adolescent physical fitness and exercise behaviors through personalized public health interventions.MethodsWe developed a hybrid Temporal–Spatial Convolutional Neural Network-Bidirectional Long Short-Term Memory (TS-CNN-BiLSTM) model. …”
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Advanced Hybrid RNN Architectures for Real-time Cryptocurrency Forecasting and Strategic Trading Optimization by Kehelwala Dewage Gayan Maduranga, Shamima Nasrin Tumpa

“…This study introduces advanced hybrid Recurrent Neural Network (RNN) architectures—LSTM-GRU, GRU-BiLSTM, and LSTM-BiLSTM—to enhance the predictive accuracy of cryptocurrency price forecasting. …”
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A Brazilian bioregionalization reappraisal based on Angiosperm distribution: a biogeographical and conservation overview by Luísa Lucresia, Thomas R. Meagher, Paulo Takeo Sano

“…Angiosperm records were compiled from online herbaria and filtered for taxonomical and geographical accuracy according to Flora e Funga do Brasil. A network analysis was performed with InfoMap Bioregions and similarity amongst recognized bioregions was evaluated with an Unweighted Pair Group Method with Arithmetic Mean. …”
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Enhanced automated art curation using supervised modified CNN for art style classification by Weiwei Li

“…To address these challenges, we developed a Modified CNN model capable of distinguishing art styles and movements using features such as color patterns, textures, and compositions. The model was trained and evaluated on a custom dataset comprising 5000 artworks representing five major art styles: Impressionism, Cubism, Realism, Abstract, and Surrealism. …”
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Machine learning for automated electrical penetration graph analysis of aphid feeding behavior: Accelerating research on insect-plant interactions. by Quang Dung Dinh, Daniel Kunk, Truong Son Hy, Vamsi Nalam, Phuong D Dao

“…This study presents a novel Machine Learning (ML) approach to automate the annotation of EPG signals. We rigorously evaluated six diverse ML models, including neural networks, tree-based models, and logistic regression, using an extensive dataset from multiple aphid feeding experiments. …”
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GaitTriViT and GaitVViT: Transformer-based methods emphasizing spatial or temporal aspects in gait recognition by Hongyun Sheng

“…Previous gait recognition methods mostly focused on constructing a sophisticated model structure for better model performance during evaluation. Moreover, these methods are primarily based on traditional convolutional neural networks (CNNs) due to the dominance of CNNs in computer vision. …”
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Crime in Tourism: A Systematic Literature Review and Bibliometric Analysis by Eylem Baş, Engin Bayraktaroğlu

“…It is also essential to evaluate crime patterns within the tourism phenomenon. …”
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A novel deep learning approach to field-road semantic segmentation by Bei Wang, Wenze Wang

“…Abstract The automatic segmentation of field-road using artificial intelligence (AI) is imperative for intelligence agriculture, allowing for the distinction between operational patterns (e.g., turning and transporting) through the analysis of global navigation satellite system (GNSS) data. …”
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Improving automated scoring of prosody in oral reading fluency using deep learning algorithm by Kuo Wang, Xin Qiao, George Sammit, Eric C. Larson, Joseph Nese, Akihito Kamata

“…This study proposed and evaluated an approach focusing on specific prosodic features using a deep-learning neural network. …”
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A Hybrid Framework Integrating Traditional Models and Deep Learning for Multi-Scale Time Series Forecasting by Zihan Liu, Zijia Zhang, Weizhe Zhang

“…The core of our approach is a novel multi-scale prediction mechanism that combines the strengths of both model types to better capture short-range patterns and long-range dependencies. We design a dual-stage forecasting process, where a classical time series component first models transparent linear trends and seasonal patterns, and a deep neural network then learns complex nonlinear residuals and long-term contexts. …”
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