Enhancing microgrid forecasting accuracy with a TCNN-TLS framework: A novel approach to mitigating uncertainty in renewable energy and load predictions by Md. Omer Faruque, Md. Majharul Islam, Md Jakaria Talukder, Arif Mia, Shahriar Tasnim, Md. Alamgir Hossain, S.M. Muyeen

“…The results demonstrate significant improvements after error adjustment, particularly in wind power and load forecasting, with notable reductions of 16.2% and 6.0% in RMSE and 17.4% and 5.7% in MAE, respectively. …”
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Thermal radiation and diffusion effects on MHD sisko fluid flow over a nonlinearly stretchable porous sheet by V. Adilakshmi, Ali Akgül, G. Venkata Ramana Reddy, Murad Khan Hassani

“…For example, elevating the Sisko parameter from 1.0 to 2.0 propels the velocity profile upward by approximately 20%, while the temperature and concentration profiles witness reductions of 10% and 8%, respectively. Moreover, escalating values of the power-law exponent and the nonlinear stretching coefficient contribute to a decline in velocity, temperature, and concentration. …”
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MetaStackD A robust meta learning based deep ensemble model for prediction of sensors battery life in IoE environment by D. Gayathri, S. P. Shantharajah

“…This work focuses on proposing a novel framework integrating pre-processing, standardization, encoding scheme, and predictive modeling that includes two algorithms, RFRImpute and MetaStackD, for predicting the RBL of sensors in any IoE device using a meta-learning-based deep ensemble approach blue for analyzing factors such as power consumption, environmental conditions, operational frequency, and workload patterns. …”
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Optimized Spectral and Spatial Design of High-Uniformity and Energy-Efficient LED Lighting for Italian Lettuce Cultivation in Miniature Plant Factories by Zihan Wang, Haitong Huang, Mingming Shi, Yuheng Xiong, Jiang Wang, Yilin Wang, Jun Zou

“…To address spatial light heterogeneity, a particle swarm optimization (PSO) algorithm was employed to determine the optimal LED arrangement, which increased the photosynthetic photon flux density (PPFD) uniformity from 83% to 93%. …”
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Advancing Evapotranspiration Modeling With Optimized Soil and Canopy Resistance Combinations by Jinfeng Zhao, Shikun Sun, Yali Yin, Yihe Tang, Chong Li, Yongshan Liang, Yubao Wang, Alexander Winkler, Shijie Jiang

“…Using eddy covariance data from 119 FLUXNET sites and the latest ET products, we find that the Ball‐Berry‐Leuning method, unified stomatal method, and RL empirical method provide comparable and top‐ranked performance across plant functional types (PFTs) and climate zones, with only a single free parameter calibrated by genetic algorithm. The power function method (S2), sensitive to soil surface water content proves to be the most effective for modeling Es, particularly in water‐limited regions. …”
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Early Detection of Mental Health Disorders based on Sentiment using Stacking Method by Naufal Maldini, Danang Wahyu Utomo, Rahmadika Putri Tresyani

“…The data underwent preprocessing steps, including cleaning, balancing, and dimensionality reduction using the TF-IDF algorithm. The study results indicate that the Stacking Classifier method achieved an accuracy of 95.66%, with a precision of 95.63%, recall of 95.66%, and F1-Score of 95.64%. …”
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Neural network compression for reinforcement learning tasks by Dmitry A. Ivanov, Denis A. Larionov, Oleg V. Maslennikov, Vladimir V. Voevodin

“…In this work, we conduct a systematic investigation of the application of these optimization techniques with popular RL algorithms, specifically Deep Q-Network and Soft Actor Critic, in different RL environments, including MuJoCo and Atari, which yields up to a 400-fold reduction in the size of neural networks. …”
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Microfluidic-enabled three-dimensional stretchable thermoelectrics by Zhenlong Huang, Tao Chen, Yan Jiang, Rui Zhou, Yizhuo Wang, Junjie Ji, Hongwei Xie, Taisong Pan, Dongpeng Fan, Linlong Liang, Longpeng Yang, Binbin Jiang, Peng Li, Min Gao, Jia Zhu, Guang Yao, Dongfeng Xue, Yuan Lin

“…The device features a 3D architecture integrating embedded microfluidics with multilayer thermoelectric networks, providing improved heat exchange capacity suitable for high thermal design power (TDP) requirements. The device achieves ~10 °C environmental and 11 °C on-skin temperature reduction with precise control. …”
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Research on auditory and olfactory regulation methods for abnormal driver emotions based on EEG signals by Bangbei Tang, Bangbei Tang, Yan Li, Yingzhang Wu, Yilun Li, Qizong Yue

“…Time-frequency domain features, including mean, variance, skewness, kurtosis, root mean square, and power spectral density, were extracted and analyzed using classification algorithms such as Back Propagation Neural Networks (BPNN), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), enabling precise identification of varying levels of tension and anger. …”
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ID List Forwarding Free Confidentiality Preserving Data Aggregation for Wireless Sensor Networks by Liehuang Zhu, Zhen Yang, Mingzhong Wang, Meng Li

“…In general, environmental data is confined to a certain range; hence, we utilize this feature and design an algorithm to help powerful base station retrieve the ID of reporting nodes. …”
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Estimating evolutionary and demographic parameters via ARG-derived IBD. by Zhendong Huang, Jerome Kelleher, Yao-Ban Chan, David Balding

“…We first demonstrate powerful inferences when true IBD information is available from simulated data. …”
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Methods and approaches of determining the boundaries of agglomerations (basic case Kharkiv region) by Kateryna Kravchenko, Kostiantyn Niemets, Kateryna Sehida, Lyudmyla Niemets, Olha Suptelo

“…The proposed algorithm was tested on the materials of Kharkiv region. …”
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High-precision position control of hydraulic support pushing system based on quasi-sliding mode by GAO Yuhao, SUN Xing, LI Yang, LIU Wei, LI Jingyan

“…At present, most position control algorithms for front hydraulic support pushing systems suffer from limited state perception dimensions and complex dynamic disturbance coupling, which limits the actual effectiveness of the control algorithms. …”
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Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning by Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar

“…The improved model not only enhanced fault detection but also contributed to a 8.03% reduction in energy loss and a 14.07% increase in power generation reliability. …”
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Preoperative diagnosis of meningioma sinus invasion based on MRI radiomics and deep learning: a multicenter study by Yuan Gui, Wei Hu, Jialiang Ren, Fuqiang Tang, Limei Wang, Fang Zhang, Jing Zhang

“…Thus, univariate logistic regression, correlation analysis, and the Boruta algorithm were applied for further feature dimension reduction, selecting radiomics and DL features highly associated with meningioma sinus invasion. …”
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Emulating real-world GLP-1 efficacy in type 2 diabetes through causal learning and virtual patients. by Calum Robert MacLellan, Hristo Petkov, Conor McKeag, Feng Dong, David John Lowe, Roma Maguire, Sotiris Moschoyiannis, Jo Armes, Simon Skene, Alastair Finlinson, Christopher Sainsbury

“…The causal AI-powered clinical trials can emulate LEAD-5 in important measurements for T2DM. …”
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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study by Hussam J. Khasawneh, Waseem M. Al-Khatib, Zaid A. Ghazal, Ahmad M. Al-Hadi, Zaid M. Arabiyat, Osama Habahbeh

“…Our approach overcomes these limitations by employing ML algorithms to accurately predict solar generation patterns, enabling more efficient scheduling of electrical appliances. …”
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Artificial intelligence may affect diversity: architecture and cultural context reflected through ChatGPT, Midjourney, and Google Maps by Ingrid Campo-Ruiz

“…Generative AI tools could jeopardise cultural diversity by prioritising some ideas and places as “cultural”, exacerbating power relationships and even aggravating segregation. …”
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An end-to-end real-time pollutants spilling recognition in wastewater based on the IoT-ready SENSIPLUS platform by Luca Gerevini, Gianni Cerro, Alessandro Bria, Claudio Marrocco, Luigi Ferrigno, Michele Vitelli, Andrea Ria, Mario Molinara

“…The data processing is based on a commercial Micro Control Unit (MCU), including an anomaly detection module, a classification module, and a false positive reduction module, all based on machine learning algorithms that have a computational complexity suitable for low-cost hardware implementation.An extensive experimental campaign on different contaminants has been carried out to train machine-learning algorithms suitable for low-cost and low-power MCU. …”
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Artificial intelligence in food system: Innovative approach to minimizing food spoilage and food waste by Helen Onyeaka, Adenike Akinsemolu, Taghi Miri, Nnabueze Darlington Nnaji, Keru Duan, Gu Pang, Phemelo Tamasiga, Samran Khalid, Zainab T. Al-Sharify, Chinenye Ugwa

“…Similarly, IKEA achieved a 30 % reduction in kitchen food waste within one year using AI-powered monitoring systems. …”
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