Evaluation of Smart Building Integration into a Smart City by Applying Machine Learning Techniques by Mustafa Muthanna Najm Shahrabani, Rasa Apanaviciene

“…The integration barriers continue due to technology, infrastructure, and operations misalignments and are escalated due to inadequate assessment frameworks and classification systems. …”
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Nowcasting Solar Irradiance Components Using a Vision Transformer and Multimodal Data from All-Sky Images and Meteorological Observations by Onon Bayasgalan, Atsushi Akisawa

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Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables by Ricardo Caetano, José Manuel Oliveira, Patrícia Ramos

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A SOH Estimation Method for Lithium-Ion Batteries Based on CPA and CNN-KAN by Kaixin Cheng, Chaolong Zhang, Kui Shao, Jin Tong, Anxiang Wang, Yujie Zhou, Zhao Zhang, Yan Zhang

“…Lithium-ion batteries are the primary power source for new energy vehicles, making accurate estimation of their state of health (SOH) essential for ensuring the safe operation of battery systems. This paper proposes a Capacity–Power Analysis (CPA) method that incorporates temperature features to enhance feature extraction across a broader range. …”
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On the influence of cross-sectional deformations on the aerodynamic performance of wind turbine rotor blades by J. Gebauer, F. Prigge, D. Ahrens, L. Wein, C. Balzani

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Design and Tests of a Large-Opening Flexible Seedling Pick-Up Gripper with Multiple Grasping Pins by Luhua Han, Meijia Zhang, Yan Wang, Guoxin Ma, Qizhi Yang, Yang Liu

“…The pick-up gripper, as a core component of automatic transplanting systems, presents challenges in reliably grasping seedlings. …”
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Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network by Shaoyang Yin, Zhaohui Chen, Wanyuan Liu, Zhiwen Su

“…Ultra-short-term charging load prediction is of crucial importance for the real-time scheduling and stable operation of power systems. To address the problem of the strong nonlinearity of power load sequences, this study proposes an ultra-short-term charging load prediction model that combines a Time Convolutional Network-Bidirectional Gated Recurrent Unit (TCN-Bi-GRU)and uses the Osprey Optimization Algorithm (OOA) based on the opposition-based learning strategy to optimize Variational Mode Decomposition (VMD). …”
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State-of-Health Estimation for Lithium-Ion Batteries Based on Lightweight DimConv-GFNet by Kehao Huang, Jianqiang Kang, Jing V. Wang, Qian Wang, Oukai Wu

“…The accurate estimation of the state of health (SOH) is crucial for effective battery management systems. This paper proposes a deep learning model dimension-wise convolutions-globalfilter networks (DimConv-GFNet) for lithium-ion battery SOH estimation. …”
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GAN-based solar radiation forecast optimization for satellite communication networks by Chao Chen, Xin Liu, Shizhong Zhao, Muhammad Bilal

“…Accurate short-term solar radiation forecasting is essential for the stable operation and dispatch of photovoltaic power generation systems. …”
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Utilising Smart-Meter Harmonic Data for Low-Voltage Network Topology Identification by Ali Othman, Neville R. Watson, Andrew Lapthorn, Radnya Mukhedkar

“…Having precise and accurate topology information is crucial for future network operations and network modelling. Topology identification approaches based on smart-meter data typically rely on Root Mean Square (RMS) voltage, current, and power measurements, which are limited in accuracy due to factors such as time resolution, measurement intervals, and instrument errors. …”
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Genotypic variations of Tamarix aphylla (L.) H.Karst. population for heavy metal phytoremediation: a case study in Markazi province, Iran by Mina Taghizadeh, Fatemeh Asghari, Mousa Solgi, Ali Khadivi

“…Trees offer a more economically viable option for remediating heavy metal-contaminated soils as their extensive root systems, substantial biomass, lower requirements, and management contribute to reduced operational costs. …”
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Discovery of an Intact Quaternary Paleosol, Georgia Bight, USA by Ervan G. Garrison, Matthew A. Newton, Benjamin Prueitt, Emily Carter Jones, Debra A. Willard

“…It is a relic paleo-land surface of sapling-sized tree stumps, root systems, and fossil animal bone exhumed by scour processes active adjacent to the artificial reef structure. …”
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Cumulative Load Forecasting in Microgrid Clusters Using Enhanced-Gated Recurrent Unit Model by Zhe-Hao Chang, Yi-Kuan Ke

“…Accurately understanding the load trends of microgrid clusters facilitates the operation of decentralized energy systems and enhances scheduling flexibility. …”
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Robust Position Control of VTOL UAVs Using a Linear Quadratic Rate-Varying Integral Tracker: Design and Validation by Omer Saleem, Muhammad Kazim, Jamshed Iqbal

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Deep Learning Forecasting Model for Market Demand of Electric Vehicles by Ahmed Ihsan Simsek, Erdinç Koç, Beste Desticioglu Tasdemir, Ahmet Aksöz, Muammer Turkoglu, Abdulkadir Sengur

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Internet of Things on Banking Processes in South Africa: A Systematic Reflection on Innovations, Opportunities and Challenges by Paul Kariuki, Lizzy Oluwatoyin Ofusori, Maria Lauda Joel Goyayi

“…The study found that while the use of IoT in banking processes is still in its infancy, most banks have enhanced their customer experiences through IoT innovations, enhanced their security systems, and enhanced their data access ecosystem to improve their operational efficiency.Moreover, the banking sector is still experiencing some challenges regarding the use of IoT in its processes, such as a lack of privacy and proper storage of customer information, limited workflow management processes, and a lack of policy framework to guide the sector as far as adoption of IoT is concerned. …”
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Explainable AI and optimized solar power generation forecasting model based on environmental conditions. by Rizk M Rizk-Allah, Lobna M Abouelmagd, Ashraf Darwish, Vaclav Snasel, Aboul Ella Hassanien

“…The XAI-based Local Interpretable and Model-independent Explanation (LIME) is adapted to identify the critical factors that influence the accuracy of the power generation forecasts model in smart solar systems. The effectiveness of the proposed X-LSTM-EO model is evaluated through the use of five metrics; R-squared (R2), root mean square error (RMSE), coefficient of variation (COV), mean absolute error (MAE), and efficiency coefficient (EC). …”
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Meta Ag: An automatic agricultural contextual metadata collection app by Md. Samiul Basir, Yaguang Zhang, Dennis Buckmaster, Ankita Raturi, James V. Krogmeier

“…Modern agricultural systems produce high-resolution data from remote sensing platforms, in-field sensors, and augmented machinery. …”
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Steady-State Model Enabled Dynamic PEMFC Performance Degradation Prediction via Recurrent Neural Network by Qiang Liu, Weihong Zang, Wentao Zhang, Yang Zhang, Yuqi Tong, Yanbiao Feng

“…Nevertheless, their widespread commercialization remains constrained by technical limitations mainly in operational longevity. Precise prognostics of performance degradation could enable real-time optimization of operation, thereby extending service life. …”
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Observer of changes in the forest of the shortest paths on dynamic graphs of transport networks by N. V. Khajynova, M. P. Revotjuk, L. Y. Shilin

“…The compactness of the representation of the observed forest of shortest paths is achieved by mapping individual trees of such a forest onto the projection of tree vertices in memory, where the position of each vertex corresponds to the distance from the tree root. The proposed version of the construction of the search procedure is based on the mechanisms existing in database management systems for creating different relational representations of the physical data model. …”
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