Doctor's husband'was watching X-rated videos in his house while daughter, 2, died in roasting car outside' Florida's housing market is flashing a warning for the rest of the US Now scientists redefine'obese' - and they've made up to 60% more people'fat' Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about'missing' model... as ominous texts emerge America's saddest lost soul can no longer SPEAK and spends days hitting herself'after years of unspeakable abuse by gangs of men' Shocking moment brazen gunman opens fire at Michigan businessman's Land Rover in daylight attack'You will DIE if you do not remove your breasts', doctors screamed at me. I refused and tried a new experimental therapy instead... now I'm cancer-free The world's most powerful passport revealed - as UK and USA both drop to record lows Police say they have FOUND woman seen in viral'kidnapping' video and reveal what happened to her after harrowing footage emerged Will Trump's Gaza peace deal fail? Policy expert MARK DUBOWITZ breaks down all the forces at play... and how the president can actually pull this off America's most renowned'prophet' makes startling prediction about alien'mothership' Kim Kardashian says she wasn't'emotionally or financially safe' during'toxic' marriage to Kanye West as she claims rapper hasn't contacted their children for MONTHS and has destroyed her dating life Astonishing interactive map lays bare where MILLIONS of homes will be submerged by water within a few years... are YOU at risk? Outrageous reason LA County CEO was awarded $2m payout for'hurt feelings' that'll see her take months off taxpayer-funded $570,000-a-year job Ugly divorce war between Mitt Romney's wealthy brother and estranged wife before she was found dead Full horrors of torture suffered by Noa Argamani's commando boyfriend are revealed - including how 6ft 5in hostage was beaten and kept chained in 6ft cell for a year after he tried to escape from Hamas Mother, 52, and daughter, 21, die after eating'poisoned birthday cake delivered by relative who owed them money' in Brazil Astonishing interactive map lays bare where MILLIONS of homes will be submerged by water within a few years... are YOU at risk? Millions of buildings and even more Americans could be at risk of sinking underwater by the end of the century. Researchers from McGill University in Canada warned rising sea levels, resulting from continued greenhouse gas emissions, threaten to wipe out coastal cities worldwide. Sea level rise measures the ocean's surface height over time.

The increasing focus on predicting renewable energy production aligns with advancements in deep learning (DL). The inherent variability of renewable sources and the complexity of prediction methods require robust approaches, such as DL models, in the renewable energy sector. DL models are preferred over traditional machine learning (ML) because they capture complex, nonlinear relationships in renewable energy datasets. This study examines key factors influencing DL technique accuracy, including sampling and hyperparameter optimization, by comparing various methods and training and test ratios within a DL framework. Seven machine learning methods, LSTM, Stacked LSTM, CNN, CNN-LSTM, DNN, Time-Distributed MLP (TD-MLP), and Autoencoder (AE), are evaluated using a dataset combining weather and photovoltaic power output data from 12 locations. Regularization techniques such as early stopping, neuron dropout, L1 and L2 regularization are applied to address overfitting. The results demonstrate that the combination of early stopping, dropout, and L1 regularization provides the best performance to reduce overfitting in the CNN and TD-MLP models with larger training set, while the combination of early stopping, dropout, and L2 regularization is the most effective to reduce the overfitting in CNN-LSTM and AE models with smaller training set.

Entity Set Expansion (ESE) is a valuable task that aims to find entities of the target semantic class described by given seed entities. Various Natural Language Processing (NLP) and Information Retrieval (IR) downstream applications have benefited from ESE due to its ability to discover knowledge. Although existing corpus-based ESE methods have achieved great progress, they still rely on corpora with high-quality entity information annotated, because most of them need to obtain the context patterns through the position of the entity in a sentence. Therefore, the quality of the given corpora and their entity annotation has become the bottleneck that limits the performance of such methods. To overcome this dilemma and make the ESE models free from the dependence on entity annotation, our work aims to explore a new ESE paradigm, namely corpus-independent ESE. Specifically, we devise a context pattern generation module that utilizes autoregressive language models (e.g., GPT-2) to automatically generate high-quality context patterns for entities. In addition, we propose the GAPA, a novel ESE framework that leverages the aforementioned GenerAted PAtterns to expand target entities. Extensive experiments and detailed analyses on three widely used datasets demonstrate the effectiveness of our method. All the codes of our experiments are available at https://github.com/geekjuruo/GAPA.

This article discusses several effective techniques for expert system knowledge acquisition based on the techniques that were successfully used to develop the Central Office Maintenance Printout Analysis and Suggestion System (COMPASS). Knowledge acquisition is not a science, and expert system developers and experts must tailor their methodologies to fit their situation and the people involved. Developers of future expert systems should find a description of proven knowledge-acquisition techniques and an account of the experience of the COMPASS project in applying these techniques to be useful in developing their own knowledge-acquisition procedures.