A Deep Learning Model Using Transformer Network and Expert Optimizer for an Hour Ahead Wind Power Forecasting by Anushalini Thiyagarajan, B. Sri Revathi, Vishnu Suresh

“…The renewable energy platform cannot operate without an accurate wind power forecast. The power system can better manage its supply and guarantee grid reliability with an accurate wind power forecast. …”
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Geological Heritage Site for the Rajmahal Flora at Mandro, Sahibganj, India: An Opportunity for an Integrated–Sustainable Tourism Circuit by Shreya Shrey, Ravi Shankar Chaubey, Pankaj Jaiswal

“…The plants were transported by pyroclastic volcanic activity, and the tuff and crystal-laden pumice helped preserve the fossils, including upright tree stumps with intact root systems. Such an association of floral fossils with ignimbrite is of high scientific relevance and is one of its kind in India. …”
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Application-Driven OAM Framework for Heterogeneous IoT Environments by Janez Sterle, Urban Sedlar, Miha Rugelj, Andrej Kos, Mojca Volk

“…We present a novel approach for providing a comprehensive operational picture of heterogeneous networks by collecting system information from physical, data-link, network and application layers using extended methods and mechanisms for OAM, which take into account particularities of persistent access heterogeneity and IoT. …”
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Comparative evaluation of remaining dentin thickness, canal centering ability and apical deformity between ProFit S3 and Protaper gold – A nano CT study by S. Swathi, Delphine Priscilla Antony, Pradeep Solete, Ganesh Jeevanandan, Satish Vishwanathaiah, Prabhadevi C. Maganur

“…Purpose: For the root canal treatment to be successful, the root canal system must be cleaned and shaped, and must be gradually widened from the apical to the coronal region in order to preserve dentin thickness. …”
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Response study of tower crane and elastic plate under dynamic complicated excitation. by Fu Liu, Haopeng Chen

“…Structural vibration will inevitably occur under the dynamic complicated excitations in tower crane and elastic plate system. The continuous nonlinear vibration would lead to the deterioration of the coupling state of the responses of the tower crane and the elastic plate system. …”
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Application of a KAN-LSTM Fusion Model for Stress Prediction in Large-Diameter Pipelines by Zechao Li, Shiwei Qin

“…Specifically, the proposed model attains a mean absolute error (MAE) of 0.033, a root mean square error (RMSE) of 0.035, and a coefficient of determination (R²) of 0.92, underscoring its superior accuracy and efficiency, and it can be used for the long-term prediction of stress in large-diameter pipes. …”
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STUDIES REGARDING MINIMUM SOIL TILLAGE by Anișoara DUMA COPCEA, Casiana MIHUT, Daniel POPA

“…Soil tillage has been integrant part of agriculture since times immemorial and it has helped preparing the germination bed, reducing soil compaction (to increase soil aeration and improve root system development), reducing weeding, incorporating fertilisers and amendments, and managing plant debris.…”
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Long Short-Term Memory-Based Computerized Numerical Control Machining Center Failure Prediction Model by Jintak Choi, Zuobin Xiong, Kyungtae Kang

“…Using continuous learning based on long short-term memory (LSTM), the system enables anomaly detection, failure prediction, cause analysis, root cause identification, remaining useful life (RUL) prediction, and optimal maintenance timing decisions. …”
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Full-scale wind turbine performance assessment: a customised, sensor-augmented aeroelastic modelling approach by T. H. Malik, C. Bak

“…However, traditional monitoring systems based on supervisory control and data acquisition (SCADA) data, which rely on operational data from turbines, lack effectiveness at early detection and quantification of these losses. …”
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Optimizing Bifacial Solar Modules with Trackers: Advanced Temperature Prediction Through Symbolic Regression by Fabian Alonso Lara-Vargas, Carlos Vargas-Salgado, Jesus Águila-León, Dácil Díaz-Bello

“…Accurate temperature prediction in bifacial photovoltaic (PV) modules is critical for optimizing solar energy systems. Conventional models face challenges to balance accuracy, interpretability, and computational efficiency. …”
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Design and experiment of key components for self-propelled harvester for Chinese cabbage by Yongtao Yu, Jiangtao Qi, Yanjun Li, Fuxiang Xie, Jian Song, Yang Bai

“…Based on the dynamic analysis, the flexible clamping mechanism (maximum clamping force of 152.82 N) and the double disc knife cutting system (rotation speed of 200–400 r min−1) were adopted, combined with the inclined conveyor, to achieve the whole process of clamping-root cutting-conveying integrated operation. …”
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Flood susceptibility mapping leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR by Sackdavong Mangkhaseum, Yogesh Bhattarai, Sunil Duwal, Akitoshi Hanazawa

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Application of a Phase-Change Material Heat Exchanger to Improve the Efficiency of Heat Pumps at Partial Loads by Koharu Tani, Sayaka Kindaichi, Keita Kawasaki, Daisaku Nishina

“…However, air conditioning (AC) systems often operate at low load ratios below where inverter control is effective, which reduces their energy efficiency. …”
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State of Charge Estimation for Sodium-Ion Batteries Based on LSTM Network and Unscented Kalman Filter by Xiangang Zuo, Xiaoheng Fu, Xu Han, Meng Sun, Yuqian Fan

“…With the increasing application of sodium-ion batteries in energy storage systems, accurate state of charge (SOC) estimation plays a vital role in ensuring both available battery capacity and operational safety. …”
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Structural optimisation of planetary gearbox components by Marinkovic Aleksandar, Sedak Miloš, Lazović Tatjana, Rosić Maja

“…The high-speed reduction in a relatively small space, coupled with a torque load capacity larger than that of any other standard transmission, positions planetary gear systems as one of the most vital components in gearing applications today. …”
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Enhancing Geodetic Control Points through GNSS and CORS Integration: A Case Study of Ibadan, Nigeria by Oyeyode Ajiboye Oyesiji, T.O. IDOWU, D.N. OLAYINKA-DOSUMU, I.U. NZELIBE

“…Goal and objectives: This research aimed to enhance the accuracy and reliability of the control points by incorporating Global Navigation Satellite Systems (GNSS) and Continuously Operating Reference Stations (CORS). …”
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Numerical and Experimental Investigation of Gas Turbine Rotor for Early Fault Detection by Muhammad Akhtar, Waqar Muhammad Ashraf, Nasir Hayat, Ghulam Moeen Uddin, Fahid Riaz

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Design and Testing of an Offset Straw-Returning Machine for Green Manures in Orchards by Quanzhong Zhang, Jinfei Zhao, Xiaowen Yang, Ling Wang, Guangdong Su, Xinying Liu, Chuang Shan, Orkin Rahim, Binghui Yang, Jiean Liao

“…In order to solve the problems of traditional orchard-specific green manure crushing and returning machines, such as the single operation effect, root system damage, unsustainable green manure growth, and low utilization rate, an offset crushing–furrowing–burying–straw-returning machine was designed for green manures in orchards. …”
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Design and implementation of a pneumatic machine for ergonomic greenhouse planting by Antonio García-Chica, Rosa María Chica, Julio J. Caparros-Mancera, Antonio Gimenez, J.L. Torres-Moreno

“…The system operates using compressed air to drive a pneumatic actuator that perforates the soil with dimensions suitable for plant root balls. …”
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A big data framework for short-term power load forecasting using heterogenous data by Haibo ZHAO, Zhijun XIANG, Linsong XIAO

“…The power system is in a transition towards a more intelligent, flexible and interactive system with higher penetration of renewable energy generation, load forecasting, especially short-term load forecasting for individual electric customers plays an increasingly essential role in future grid planning and operation.A big data framework for short-term power load forcasting using heterogenous was proposed, which collected the data from smart meters and weather forecast, pre-processed and loaded it into a NoSQL database that was capable to store and further processing large volumes of heterogeneous data.Then, a long short-term memory (LSTM) recurrent neural network was designed and implemented to determine the load profiles and forecast the electricity consumption for the residential community for the next 24 hours.The proposed framework was tested with a publicly available smart meter dataset of a residential community, of which LSTM’s performance was compared with two benchmark algorithms in terms of root mean square error and mean absolute percentage error, and its validity has been verified.…”
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