UAV-Based Yield Prediction Based on LAI Estimation in Winter Wheat (<i>Triticum aestivum</i> L.) Under Different Nitrogen Fertilizer Types and Rates by Jinjin Guo, Xiangtong Zeng, Qichang Ma, Yong Yuan, Nv Zhang, Zhizhao Lin, Pengzhou Yin, Hanran Yang, Xiaogang Liu, Fucang Zhang

“…The prediction results were evaluated using random forest (RF), support vector machine (SVM) and back propagation neural network (BPNN) methods to select the optimal spectral index and establish yield prediction models. …”
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Exploring the Relationship between Spatiotemporal Distribution of Urban Vibrancy and Neighborhood Attributes by Coupling Multi-Source Data: A Case of Nanshan District in Shenzhen by Liu Feng, Tang Zhong, Zhang Liang, Yu Lingmin, Liu Ke

“…This work focuses on the Nanshan District of Shenzhen City as the study area, and has three objectives: (i) one-week passenger flow data that characterized the spatiotemporal distribution of urban vibrancy were provided; (ii) broadly collected Street View Images (SVI) were incorporated as a visional environmental factor, together with functional and morphological factors, into understanding the influencing mechanism of urban vibrancy; and finally, (iii) machine learning tools were employed to apply the Random Forest Regression (RFR) algorithm in exploring the independent driving role of the characteristic factors behind the temporal distribution of urban vibrancy, and the Geographically Weighted Regression (GWR) model was used to probe the influence of the characteristic factors on the spatial distribution of this dynamic concept. …”
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Research Progress and Prospect of Green Infrastructure with Public Health Promotion Function by Tongyu LI, Junyi LIXU, Binxia XUE, Yan (USA) SONG

“…Such a framework could significantly enhance urban planning and policy-making by optimizing GI interventions to provide the most significant public health benefits. …”
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Accurate prediction of damage depth of multi-story structural footings with Matlab implementation by Ang LI, Weidong WANG, Qian MOU, Feng WANG, Zhenghe MA, Lei ZHAO, Gang HUANG, Yonggen ZHOU, Shengqi TIAN

“…Firstly, we construct a mechanical model of plastic slip line field of multilayer structure base plate, derive the analytical solution of base plate damage depth under multiple working conditions, and optimize five working conditions for calculating the damage depth of multilayer structure base plate; secondly, we analyze the shortage and error causes of manual calculation method of damage depth of multilayer structure base plate; we propose a logical flow for calculating the damage depth of multilayer structure base plate, and develop a system for calculating the damage depth of multilayer structure base plate with the help of Matlab language. …”
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Predicting Student Performance and Enhancing Learning Outcomes: A Data-Driven Approach Using Educational Data Mining Techniques by Athanasios Angeioplastis, John Aliprantis, Markos Konstantakis, Alkiviadis Tsimpiris

“…The results indicated that courses with strong correlations (+0.3 and above) significantly enhanced predictive accuracy, particularly in binary classification tasks. kNN and neural networks emerged as the most robust models, achieving F1 scores exceeding 0.8. These findings underscore the potential of EDM to optimize instructional strategies and support personalized learning pathways. …”
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Automated Microfluidic Platform for High‐Throughput Biosensor Development by Shitanshu Devrani, Daniel Tietze, Alesia A. Tietze

“…Combining these methods enhances machine learning models for Cu2+ concentration prediction, achieving receiver operating characteristic area under the curve values exceeding 95%.…”
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Applying Semi-AutoML for Vessel Traffic Flow Prediction: Case Studies of Two Ports by Abdeltif Boujamza, Mohamed El Hafta, Saâd Lissane Elhaq, Ahmed Loukili

“…This is followed by a manual tuning phase to further optimize the performance of the selected models. The proposed methodology is implemented on limited-scale datasets from two separate case studies: Mohammedia port and Los Angeles port, with the latter serving as a benchmark against an existing study. …”
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Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…Histograms are widely used for summarizing data distributions, detecting anomalies, and improving machine learning models’ accuracy. However, traditional histogram-based methods require access to raw data, raising privacy concerns, particularly in sensitive IoT applications. …”
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Numerical and Experimental Study of Fluid Flow and Heat Transfer in Porous Media: A Review Article by Ramin Ranjbarzadeh, Giuseppe Sappa

“…Additionally, the review highlights emerging methodologies, including advanced pore-scale modeling, the lattice Boltzmann method, and machine learning, as transformative tools for overcoming existing limitations and exploring future directions. …”
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A simulation based approach for enhancing automatic detection of cicada songs in challenging chorus conditions by Ryotaro Okamoto, Hiroyuki Oguma

“…The proposed method achieved a 22% improvement in F1-score compared to models trained on focal recordings alone. By optimizing simulation parameters through hyperparameter tuning, we achieved a mean F1-score of 0.83 on real-world soundscape recordings with minimal training data (approximately 10 focal recordings per species). …”
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A Novel Active RFID and TinyML based system for livestock Localization in Pakistan by Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali

“…To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies …”
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AI-assisted early screening, diagnosis, and intervention for autism in young children by Sijun Zhang

“…Artificial intelligence (AI) combined with machine learning is being used to improve the efficiency of early screening, diagnosis, and intervention of autism in young children. …”
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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…To facilitate this, an automated artificial intelligence material recommendation mechanism was developed, underpinned by several machine learning models. By observing online user learning behavior patterns, learning data and indicators were formulated, enabling the analysis of various online learning behaviors (e.g., watching videos and answering practice questions) and the generation of learning processes that can be viewed by learners. …”
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A Hybrid Framework for Soil Property Estimation from Hyperspectral Imaging by Daniel La’ah Ayuba, Jean-Yves Guillemaut, Belen Marti-Cardona, Oscar Mendez

“…HyperSoilNet leverages a pretrained hyperspectral-native CNN backbone and integrates it with a carefully optimized machine learning (ML) ensemble to combine the strengths of deep representation learning with traditional ML techniques. …”
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A large multisite lipidomic investigation of parity and aging in dairy cows by David B. Sheedy, Helen M. Golder, Sergio C. Garcia, Zhiqian Liu, Peter Moate, Priyanka Reddy, Simone J. Rochfort, Jennie E. Pryce, Ian J. Lean

“…Variation in lipid profiles were mostly attributed to farm of origin (36%–41% of variation), with feeding system explaining 13% to 21% and parity explaining 6% to 9%, according to ANOVA simultaneous component analysis modeling. Multiple linear regression and orthogonal partial least squares (O-PLS) investigated the association of the lipid profile with age (d), whereas discriminant analysis compared first parity with >3 parity cows in O-PLS discriminant analysis, random forest, and support vector machine models. …”
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Orchard-Wide Visual Perception and Autonomous Operation of Fruit Picking Robots: A Review by CHEN Mingyou, LUO Lufeng, LIU Wei, WEI Huiling, WANG Jinhai, LU Qinghua, LUO Shaoming

“…Improved adaptation techniques, possibly through machine learning models that can learn and adjust to different environmental conditions, are suggested as a way forward. …”
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Influence of casting parameters on the surface and mechanical properties of leaded brass alloys: mechanistic insights by Maryama Hammi, Khadija El Bourakadi, Mohammed Dahhou, Charaf Lazrak, Abderrahim Eddaoui, Amine El haimeur

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Development of a clinical decision support system for breast cancer detection using ensemble deep learning by Jasjeet Kaur Sandhu, Chetna Sharma, Amandeep Kaur, Saroj Kumar Pandey, Anurag Sinha, J. Shreyas

“…This research discusses the creation of a unique Deep Learning (DL) Ensemble Deep Learning based on a Clinical Decision Support System (EDL-CDSS) that enables the precise and expeditious diagnosis of breast cancer. Numerous DL models are combined in the proposed EDL-CDSS to create an ensemble method that optimizes the advantages and reduces the disadvantages of individual techniques. …”
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Optimum Design of a Savonius VAWT for Implementation in Urban Places having Low to Medium Wind Velocities by Dutta Animesh, Singh Harshvardhan, Rai Gaurav Kumar, Bose Anirban

“…Enhancements in performance have been examined, leading to the optimization of several design parameters. The ultimate objective is to develop an optimal VAWT design that surpasses the performance of earlier models and is suitable for use in urban environments where wind velocities fluctuate within the low to medium range.…”
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Progress on the application of supercomputer brain simulation technology by SUN Zhe

“…It also surveys prominent simulation platforms such as NEST, NEURON, and The Virtual Brain (TVB), highlighting their strengths in modeling spiking neuronal network (SNN), multicompartmental neurons, and large⁃scale functional connectivity, respectively. …”
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