Assessing the reliability of species distribution models under changing environments: A case study on cetaceans in the North-East Atlantic by Rémi Pigeault, Matthieu Authier, Nadya C. Ramirez-Martinez, Auriane Virgili, Steve C.V. Geelhoed, Jan Haelters, Maite Louzao, Camilo Saaveedra, Anita Gilles

“…These predictions are more uncertain and warrant caution. 5. Synthesis and applications: extrapolations and nearby data highlighted environmental gaps to predict cetacean distributions in the North-East Atlantic, which could be covered by future surveys. …”
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Vapor pressure deficit (VPD) downscaling based on multi-source remote sensing, in-situ observation, and machine learning in China by Mi Wang, Zhuowei Hu, Xiangping Liu, Wenxing Hou

“…The high accuracy demonstrated in year-to-year and station-to-station experiments, coupled with the strong consistency between RF-VPD data and in-situ observations, underscores the robustness and applicability of RF-VPD models in capturing spatiotemporal patterns. …”
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Automated Ledger or Fintech Analytics Platform? by Andrew Kumiega

“…Initially designed as an automated ledger tool, Excel swiftly evolved into a data analytics platform for financial analysts to execute intricate financial analyses. …”
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Spatial Pattern and Influencing Factors of Tourist Attractions in Coastal Cities: A Case Study of Qingdao by Yue Xu, Xuliang Zhang, Kuncheng Zhang, Jing Yu, Jia Liu

“…The findings are broadly applicable to other coastal tourist cities and offer strategic insights for sustainable development in such contexts.…”
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Ethereum Blockchain Interconnectivity for Dynamic and Privacy-Preserving Access Control by Christian Delgado-von-Eitzen, Manuel Jose Fernandez-Iglesias, Luis Anido-Rifon, Martin Llamas-Nistal

“…The proposed solution addresses key limitations in existing blockchain infrastructures and offers a flexible, decentralized framework suitable for applications requiring robust data governance and regulatory compliance.…”
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NICAM–LETKF JAXA Research Analysis (NEXRA) Version 2.0 by Shuhei Matsugishi, Ying‐Wen Chen, Koji Terasaki, Kaya Kanemaru, Shunji Kotsuki, Hisashi Yashiro, Kosuke Yamamoto, Masaki Satoh, Takuji Kubota, Takemasa Miyoshi

“…This dataset is produced using the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and the Local Ensemble Transform Kalman Filter (LETKF)‐based atmospheric data assimilation system. The system assimilates in situ atmospheric observations, satellite data, and satellite‐derived precipitation data into global atmospheric simulations. …”
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A trusted decision fusion ship recognition method based on improved evidence theory by XU Zhiyang, LIU Jun, CHEN Shuai, LI Shuangshuang, ZHOU Jihao, HAN Li, ZHANG Jie, XUE Anke, PENG Dongliang

“…It has achieved quantitative evaluation of recognition results, which objectively meets the needs of practical applications.…”
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The pipelines of deep learning-based plant image processing by Kaiyue Hong, Yun Zhou, Han Han

“…Recent advancements in data science and artificial intelligence have significantly transformed plant sciences, particularly through the integration of image recognition and deep learning technologies. …”
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Twinning the path of digital building permits and digital building logbooks – Diagnosis and challenges by Pedro Mêda, Judith Fauth, Christian Schranz, Hipólito Sousa, Harald Urban

“…While DBP and DBL can function independently, their full potential is realised through a cohesive framework that supports continuous data updates and stakeholder collaboration, facilitating the “golden thread” of information essential for effective digital twin applications. …”
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The Impact of Artificial Intelligence (AI) for Transforming Tourism Marketing on the USA Industry Practices by Raghib Abid, Palash Saha, Md. Mominul Islam

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Enhancing Building-Integrated Photovoltaic Power Forecasting with a Hybrid Conditional Generative Adversarial Network Framework by Dong Ha Choi, Wei Li, Albert Y. Zomaya

“…These results highlight the potential of our framework to enhance prediction accuracy and optimize data utilization in renewable energy applications.…”
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EXPLORE THE HISTORICAL MATERIALIST PERSPECTIVE ON THE ALIENATION OF LABOUR IN THE CURRENT DIGITAL AGE by Nguyen Van Sang

“…This connection highlights the study's contemporary relevance and practical applicability.…”
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A bayesian network model for neurocognitive disorders digital screening in Chinese population: development and validation study by Yifan Yu, Shuaijie Zhang, Hongkai Li, Fuzhong Xue

“…The calibration curves were well calibrated, and the decision curve analysis demonstrated its clinical applicability. In sensitivity analysis, the AUC of the Bayesian network model was 0.791 (95% CI; 0.777-0.806), with good robustness to missing data. …”
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Time Series Anomaly Detection Using Signal Processing and Deep Learning by Jana Backhus, Aniruddha Rajendra Rao, Chandrasekar Venkatraman, Chetan Gupta

“…Our experiments on several benchmark datasets demonstrate that bandpass filtering consistently improves the performance of deep learning methods, including the Functional Neural Network Autoencoder, by refining the input data. Our proposed approach achieves superior performance of up to 20% in detecting anomalies, particularly in a time series with intricate structures, highlighting its potential for practical applications in multiple domains.…”
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Federated learning with joint server-client momentum by Boyuan Li, Shaohui Zhang, Qiuying Han

“…In this study, we introduce a novel Federated Learning algorithm called Federated Joint Server-Client Momentum (FedJSCM) to address data heterogeneity in real-world Federated Learning applications. …”
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Recovering manifold representations via unsupervised meta-learning by Yunye Gong, Jiachen Yao, Ruyi Lian, Xiao Lin, Chao Chen, Ajay Divakaran, Yi Yao

“…Manifold representation learning holds great promise for theoretical understanding and characterization of deep neural networks' behaviors through the lens of geometries. However, data scarcity remains a major challenge in manifold analysis especially for data and applications with real-world complexity. …”
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Reimagining language learning: AI-driven innovations for engagement and growth by Bradford J. Lee

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Design and implementation of CMUT multi-channel ultrasonic transceiver board based on PXIe by Wu Shuaiqi, He Changde, Sun Shuaiwen, Lu Xiaoxing, Zhang Guojun, Zhang Wendong

“…To enable multi-channel pulse transmission, data acquisition, storage, transmission, and analysis based on a capacitive micromachined ultrasonic transducer (CMUT) array, a 32-channel ultrasound transceiver board was designed based on the PXIe bus. …”
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Deep Learning-Based Remote Sensing Image Analysis for Wildfire Risk Evaluation and Monitoring by Shiying Yu, Minerva Singh

“…Although deep learning models outperform traditional methods in predicting wildfires, their accuracy drops to about 90% when using remotely sensed data. To effectively monitor and predict fires, this project aims to develop deep learning models capable of processing multivariate remotely sensed global data in real time. …”
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Modeling of biodiesel production using optimization designs from literature: aiming to reduce the laboratory workload by Iver Bergh Hvidsten, Kristian Hovde Liland, Oliver Tomic, Jorge Mario Marchetti

“…These models offer researchers a data-driven approach to selecting and optimizing biodiesel reactions, reducing laboratory time and improving predictive accuracy for specific systems.…”
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