ENHANCING WEIGHTED FUZZY TIME SERIES FORECASTING THROUGH PARTICLE SWARM OPTIMIZATION by Armando Jacquis Federal Zamelina, Suci Astutik, Rahma Fitriani, Adji Achmad Rinaldo Fernandes, Lucius Ramifidisoa

“…Furthermore, the length of the interval and the extent to which previous values (Order length) are utilized in predicting the subsequent value are pivotal factors in WFTS modelization and its forecasting accuracy. …”
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Novel transfer learning based bone fracture detection using radiographic images by Aneeza Alam, Ahmad Sami Al-Shamayleh, Nisrean Thalji, Ali Raza, Edgar Anibal Morales Barajas, Ernesto Bautista Thompson, Isabel de la Torre Diez, Imran Ashraf

“…In this study, we propose a novel transfer learning-based approach called MobLG-Net for feature engineering purposes. Initially, the spatial features are extracted from bone X-ray images using a transfer model, MobileNet, and then input into a tree-based light gradient boosting machine (LGBM) model for the generation of class probability features. …”
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Observation and Numerical Simulation of Cross-Mountain Airflow at the Hong Kong International Airport from Range Height Indicator Scans of Radar and LIDAR by Ying Wa Chan, Kai Wai Lo, Ping Cheung, Pak Wai Chan, Kai Kwong Lai

“…In order to study the feasibility of predicting such disturbed airflow, a mesoscale meteorological model and a computational fluid dynamics model with high spatial resolution are used in this paper. …”
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Deep Learning-Based MRI Brain Tumor Segmentation With EfficientNet-Enhanced UNet by Pradeep Kumar Tiwary, Prashant Johri, Alok Katiyar, Mayur Kumar Chhipa

“…Precisely delineating brain tumor areas from multimodal MRI scans is crucial for clinical diagnosis and predicting patient outcomes. However, challenges arise from similar intensity patterns, varying tumor shapes, and indistinct boundaries, which complicate brain tumor segmentation. …”
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Association between land use features and changes in walking patterns from pre-pandemic to post-pandemic: A case study of city of Sydney (2013–2023) by Fatemeh Nourmohammadi, Zahra Nourmohammadi, Tanapon Lilasathapornkit, Meead Saberi

“…The observed changes in pedestrian activities are, however, spatially heterogeneous. Modeling results reveal that areas with greater commercial land use, more points of interest (POIs), higher population density, and higher network connectivity experienced a significant negative change in the number of walking trips from the pre-pandemic to the pandemic period. …”
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La nouvelle insertion de l’agriculture urbaine dans la fabrication de la ville by Gustavo Nagib

“…This article addresses this theme following research conducted between 2018 and 2021 in Greater Paris, where UA has integrated as a model of edible landscaping, educational vegetable gardening or urban farming. …”
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Real-Time Fire Risk Classification Using Sensor Data and Digital-Twin-Enabled Deep Learning by In-Seop Na, Vani Rajasekar, Velliangiri Sarveshwaran

“…A key innovation is the use of digital twin technology, which dynamically integrates real-time data from IoT sensors and simulation models to predict fire disaster scenarios accurately. …”
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Estimating corn leaf chlorophyll content using airborne multispectral imagery and machine learning by Fengkai Tian, Jianfeng Zhou, Curtis J. Ransom, Noel Aloysius, Kenneth A. Sudduth

“…A UAV-based multispectral camera collected imagery at the same time as manual readings. Machine learning models developed based on image features derived from UAV images were used to predict leaf chlorophyll content. …”
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Assessing the Impact of Land Use and Land Cover Change on Environmental Parameters in Khyber Pakhtunkhwa, Pakistan: A Comprehensive Study and Future Projections by Mehjabeen Khan, Ruishan Chen

“…Projections for 2100 predict LST rising to 55.3 °C, with NDVI, MNDWI, and NDMI dropping to 0.36, 0.17, and 0.21, respectively. …”
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Generative Design-Driven Optimization for Effective Concrete Structural Systems by Hossam Wefki, Mona Salah, Emad Elbeltagi, Majed Alinizzi

“…The model automates and optimizes the layout process, yielding measurable improvements in spatial efficiency while maintaining compliance with structural performance criteria. …”
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Infilling of missing rainfall radar data with a memory-assisted deep learning approach by J. Meuer, L. M. Bouwer, L. M. Bouwer, F. Kaspar, R. Lehmann, W. Karl, T. Ludwig, C. Kadow

“…This novel approach represents a step forward in hydrological applications, potentially improving the way we predict and manage water-related events by increasing the accuracy and reliability of precipitation data analysis.…”
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Incorporating long-term numerical weather forecasts to quantify dynamic vulnerability of irrigation supply system: A case study of Shihmen Reservoir in Taiwan by Chia-Chuan Hsu, Yu-Pin Lin

“…The simulation of historical conditions shows successful predictions of 6 out of 7 historical drought-induced irrigation stoppages during 2000–2021. …”
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Basin-wide and coastal modes of north tropical Atlantic variability have distinct impacts on hurricanes by Yi Liu, Michael J. McPhaden, Wenju Cai, Yu Zhang, Jiuwei Zhao, Hyacinth C. Nnamchi, Xiaopei Lin, Ziguang Li, Jun-Chao Yang

“…Here we use observations and model outputs over the past several decades to determine whether there exists inherent diversity in north tropical Atlantic surface temperature spatial structures and impacts. …”
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Forecasting the Influence of Climate Change on Agroecosystem Services: Potential Impacts on Honey Yields in a Small-Island Developing State by Diana L. Delgado, María Eglée Pérez, Alberto Galindo-Cardona, Tugrul Giray, Carla Restrepo

“…The four models varied in terms of their predictions but showed that both honey yields and areas suitable for honey production will decrease under scenarios of climate change. …”
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Boundary-Aware Transformer for Optic Cup and Disc Segmentation in Fundus Images by Soohyun Wang, Byoungkug Kim, Doo-Seop Eom

“…Furthermore, the proposed model more accurately captures the relative size and spatial alignment of the OD and OC and produces smooth and consistent boundary predictions in clinically significant regions such as the region of interest (ROI). …”
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A method to quantify jump dispersal of invasive species from occurrence data: the case of the spotted lanternfly, Lycorma delicatula by Nadège Belouard, Sebastiano De Bona, Matthew R. Helmus, Isabella G. Smith, Jocelyn E. Behm

“…The accuracy of predicting the spread of biological invasions is improved if models explicitly incorporate the two main dispersal mechanisms: diffusive spread and jump dispersal. …”
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Role of Cairns–Gurevich ion distribution on nonlinear wave propagation in negatively charged dusty plasma by N.S. Alharthi

“…The results demonstrated that soliton waves, explosive waves, and kink waves exhibit distinct behaviors depending on these parameters and the spatial context of Earth's magnetosphere. These findings provide new insights compared to previous studies into the conditions under which these waveforms emerge and evolve, especially in magnetized environments where earlier models were less effective at accurately characterizing or predicting wave behavior. …”
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Micro, Small or Medium, New or Old—Are There Differences? Testing Business-Specific Difficulties by Mihaela Brîndușa Tudose, Savin Dorin Ionesi, Ionuț Dulgheriu, Liliana Buhu, Valentina Diana Rusu

“…To formulate general conclusions or predictions, in economic research, large databases are often used, related to more or less homogeneous samples, without taking into account the spatial or structural differences of the analysed processes or phenomena. …”
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Joint Inversion of InSAR and GNSS for surface subsidence and terrestrial water storage anomalies of small-area in west-central Yunnan Province, China by Ming Shangguan, Jingyi Guo, Shuguang Wu, Xu Zhou, Rong Zou, Xin Zhang

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Land Use and Climate Change Accelerate the Loss of Habitat and Ecological Corridor to Reeves's Pheasant (Syrmaticus reevesii) in China by Qingqing He, Shan Tian, Junqin Hua, Zhengxiao Liu, Yating Liu, Ting Jin, Jiliang Xu

“…However, determining the causal factors of their extinction and carrying out protection measures appear to be challenging owing to a lack of long‐term data with high spatial and temporal resolutions. Here, based on a national field survey, we used habitat suitability models and integrated data on geographical environment, road development, land use, and climate change to predict the potential changes in the distribution and connectivity of the habitat of Reeves's pheasant from 1995 to 2050. …”
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