Unlocking insights: A systematic review of contextualized cubing instructional strategies by Sam Ramaila

“…Drawing from a range of studies, including experimental interventions, comparative analyses, and qualitative investigations, key themes emerged regarding the benefits of contextualized instruction in enhancing learners' understanding of cubing algorithms, spatial visualization abilities, and overall problem-solving competence. …”
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Optimized intelligent learning for groundwater quality prediction in diverse aquifers of arid and semi-arid regions of India by Imran Khan, Sarwar Nizam, Apoorva Bamal, Abdul Majed Sajib, Mir Talas Mahammad Diganta, Mohd Azfar Shaida, S.M. Ashekuzzaman, Stephen Nash, Agnieszka I. Olbert, Md Galal Uddin

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Innovative Expert-Based Tools for Spatiotemporal Shallow Landslides Mapping: Field Validation of the GOGIRA System and Ex-MAD Framework in Western Greece by Michele Licata, Francesco Seitone, Efthimios Karymbalis, Konstantinos Tsanakas, Giandomenico Fubelli

“…Field-based landslide mapping is a crucial task for geo-hydrological risk assessment but is often limited by the lack of integrated tools to capture accurate spatial and temporal data. This research investigates a Direct Numerical Cartography (DNC) system’s ability to capture both spatial and temporal landslide features during fieldwork. …”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…The Listener Acoustic Personalisation (LAP) challenge 2024 aimed at advancing research in spatial audio personalisation, with a focus on head-related transfer functions (HRTFs). …”
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Hybrid intelligent watermark System by Fardos Abdalkader, Shahbaa Khaleel, Nada Saleem

“…The method indicates hiding the watermark in both spatial and frequency domains using Artificial Intelligent techniques, such as neural networks and genetic algorithms by dividing the watermark depending on the important information contents. …”
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Estimating Chlorophyll-<i>a</i> and Phycocyanin Concentrations in Inland Temperate Lakes across New York State Using Sentinel-2 Images: Application of Google Earth Engine for Effic... by Sara Akbarnejad Nesheli, Lindi J. Quackenbush, Lewis McCaffrey

“…In situ sampling is used to assess water quality, but such observations are time intensive and therefore practically limited in their spatial extent. Previous research has used remote sensing imagery to estimate phytoplankton pigments (typically chlorophyll-<i>a</i> or phycocyanin) as HAB indicators. …”
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Zonal Estimation of the Earliest Winter Wheat Identification Time in Shandong Province Considering Phenological and Environmental Factors by Jiaqi Chen, Xin Du, Chen Wang, Cheng Cai, Guanru Fang, Ziming Wang, Mengyu Liu, Huanxue Zhang

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Assessing the Effect of Water on Submerged and Floating Plastic Detection Using Remote Sensing and K-Means Clustering by Lenka Fronkova, Ralph P. Brayne, Joseph W. Ribeiro, Martin Cliffen, Francesco Beccari, James H. W. Arnott

“…Although remote sensing has been used to map large floating plastic rafts, there are research gaps in detecting submerged plastic due to the limited amount of in situ data. …”
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Study on the inversion and spatiotemporal variation mechanism of soil salinization at multiple depths in typical oases in arid areas: A case study of Wei-Ku Oasis by Jinming Zhang, Jianli Ding, Zihan Zhang, Jinjie Wang, Xu Zeng, Xiangyu Ge

“…The R² values for the test set of soil salinity prediction models at 10–20 cm, 20–40 cm, 40–60 cm, 60–80 cm, and 80–100 cm depths are 0.5, 0.57, 0.53, 0.5, and 0.52, respectively. (2) Based on soil salinity classification, the area of non-salinized soil at all depths shows an increasing trend, whereas non-salinized soil within the oasis exhibits salinity accumulation. (3) Soil salinity in the Wei-Ku Oasis is influenced by multiple types of driving factors, with the interaction of any two factors enhancing the explanatory power for salinity changes. Future research could also focus on more refined soil salinity mapping across seasons, obtaining more comprehensive driving data with higher temporal and spatial resolutions, analyzing the transfer mechanisms of soil salinity between different soil depths, and providing a theoretical basis for the scientific management of salinization.…”
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Spatio-Temporal Generalization of VIS-NIR-SWIR Spectral Models for Nitrogen Prediction in Sugarcane Leaves by Carlos Augusto Alves Cardoso Silva, Rodnei Rizzo, Marcelo Andrade da Silva, Matheus Luís Caron, Peterson Ricardo Fiorio

“…Conducted in three regions of São Paulo, Brazil (Jaú, Piracicaba and Santa Maria), the research involved three experiments, one per location. …”
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Evaluation of stroke sequelae and rehabilitation effect on brain tumor by neuroimaging technique: A comparative study. by Xueliang Guo, Lin Sun

“…The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. The Bra2020 dataset is utilized to assess the accuracy of the proposed deep learning neural network. …”
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Results of parallel independent visual evaluation of projective cover of the bottom during macrophyte assesment survey by A. A. Dulenin

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Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles by Fatma S. Alrayes, Nazir Ahmad, Asma Alshuhail, Menwa Alshammeri, Ali Alqazzaz, Hassan Alkhiri, Jehad Saad Alqurni, Yahia Said

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Critical soil moisture detection and water–energy limit shift attribution using satellite-based water and carbon fluxes over China by Y. Liu, J. Xiao, X. Li, Y. Li

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Geoinformatics and Machine Learning for Shoreline Change Monitoring: A 35-Year Analysis of Coastal Erosion in the Upper Gulf of Thailand by Chakrit Chawalit, Wuttichai Boonpook, Asamaporn Sitthi, Kritanai Torsri, Daroonwan Kamthonkiat, Yumin Tan, Apised Suwansaard, Attawut Nardkulpat

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Prediction method of gas content in deep coal seams based on logging parameters: A case study of the Baijiahai region in the Junggar Basin by Yijie Wen, Shu Tao, Fan Yang, Yi Cui, Qinghe Jing, Jie Guo, Shida Chen, Bin Zhang, Jincheng Ye

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A Low Complexity Linear Precoding Method for Extremely Large-Scale MIMO Systems by Salah Berra, Abderrazak Benchabane, Sourav Chakraborty, Kazuki Maruta, Rui Dinis, Marko Beko

“…As a result, spatial non-stationary features emerge as users view just a section of the antenna array, known as the visibility regions (VRs). …”
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STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG by Raquel Fernández-Martín, Alfonso Gijón, Odile Feys, Elodie Juvené, Alec Aeby, Charline Urbain, Xavier De Tiège, Vincent Wens

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Optimizing the Finishing Treatment of Potato Harvester Transmission Shafts by A. V. Nemenko, M. M. Nikitin

“…The potato harvester’s distinctive specifications include the spatially segregated drive of its units from an external engine, operating under stochastic conditions. …”
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DBANet: a dual-branch convolutional neural network with attention enhancement for motor imagery classification by Dandan Liang, Brendan Z. Allison, Ruiyu Zhao, Andrzej Cichocki, Jing Jin

“…Finally, the combined features are applied for classification.Results The subject-dependent results of our proposed framework on the three datasets (BCI Competition IV dataset 2b, 2a and ECUST dataset) are 85.19%, 85.15% and 75.24%, respectively.Comparison with existing methods We conduct an extensive study between the proposed framework and five State-of-the-Art models, including FBCSP, ShallowConvNet, EEGNet, FBCNet, and IFNet.Conclusions for research articles We certificate the superiority of the proposed framework by conducting comparative experiments on three datasets with advanced MI decoding algorithms.…”
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