Personalized news recommendation can alleviate the information overload problem, and accurate modeling of user interests is the core of personalized news recommendation. Existing news recommendation methods integrate the titles and contents of news a...
Road intersections are essential to road networks. How to precisely recognize road intersections based on GPS data is still challenging in intelligent transportation systems. Road intersection recognition involves detecting intersections and recogniz...
N-terminal pro-brain natriuretic peptide (NT-proBNP) and uric acid are elevated in pregnancies with preeclampsia (PE). Short-term prediction of PE using angiogenic factors has many false-positive results. Our objective was to validate a machine-learn...
In the field of meteorology, radiosonde data and observation data are critical for analyzing regional meteorological characteristics. Because of the high false alarm rate, severe convection forecasting is still challenging. In addition, the existing...
Accurate sales forecasting can provide a scientific basis for the management decisions of enterprises. We proposed the xDeepFM-LSTM combined forecasting model for the characteristics of sales data of apparel retail enterprises. We first used the Extr...
High efficiency and safety are critical factors in ensuring the optimal performance and reliability of systems and equipment across various industries. Fault monitoring (FM) techniques play a pivotal role in this regard by continuously monitoring sys...
In recent years, deep learning has been applied to the field of recommendation, which can learn complex user interaction features and make better recommendations. However, deep learning only focuses on the interaction of high-order features and negle...
This study presents a data-driven model for identifying failure modes (FMs) and predicting the corresponding punching shear resistance of slab-column connections with shear reinforcement. An experimental database that contains 328 test results is use...
Chlorophyll fluorescence is a useful indicator of a plant’s physiological status, particularly under stress conditions. Remote sensing is an increasingly adopted technology in modern agriculture, allowing the acquisition of crop information (e....
Knowledge graph (KG) helps to improve the accuracy, diversity, and interpretability of a recommender systems. KG has been applied in recommendation systems, exploiting graph neural networks (GNNs), but most existing recommendation models based on GNN...
The Recommender System (RS) has obtained a pivotal role in e-commerce. To improve the performance of RS, review text information has been extensively utilized. However, it is still a challenge for RS to extract the most informative feature from a tre...
To realize the real-time measurement of masses of nanoparticles, virus molecules, organic macromolecules, and gas molecules, and to analyze their physical and chemical properties, a ZnO nanowire (NW) resonator operating at room temperature with an ul...
China’s FengYun 3E (FY3E) meteorological satellite, launched in 2021, is equipped with advanced instruments for comprehensive Earth observations. In this study, we compared outgoing longwave radiation (OLR) measurements from the FY3E satellite...
Under variable working conditions, the tool status signal is affected by changing machine processing parameters, resulting in a decreased prediction accuracy of the remaining useful life (RUL). Aiming at this problem, a method based on multi-sensor f...
Musculoskeletal injury (MSI) risk screening has gained significant attention in rehabilitation, sports, and fitness due to its ability to predict injuries and guide preventive interventions. This review analyzes the Functional Movement Screen (FMS) a...
Water quality prediction plays a crucial role in both enterprise management and government environmental management. However, due to the variety in water quality data, inconsistent frequency of data acquisition, inconsistency in data organization, an...
Preeclampsia (PE) is not merely a pregnancy complication but a clinical manifestation of underlying vascular dysfunction with long-term health implications. It is diagnosed after 20 weeks of gestation as new-onset hypertension with proteinuria or org...
The study intended to utilizing waste organic fiber for low-cost semi-flexible substrate fabrication to develop microstrip patch antennas for low band communication applications. All the semi-flexible substrates (12.2 wt. % OPEFF/87.8 wt. % PCL, 12.2...
Predicting art auction results presents a unique challenge due to the complexity and variability of factors influencing artwork prices. This study explores a range of machine learning architectures designed to forecast auction outcomes using tabular...
An accurate forecast of typhoon tracks is crucial for disaster warning and mitigation. However, existing numerical weather prediction models, such as the Weather Research and Forecasting (WRF) model, still exhibit significant errors in track forecast...
Move method refactoring (MMR) is one of the most commonly used software maintenance techniques to improve feature envy. Existing works focus on how to identify and recommend MMR. However, little is known about how MMR impacts program performance. The...
CTR (Click-Through Rate) prediction has attracted more and more attention from academia and industry for its significant contribution to revenue. In the last decade, learning feature interactions have become a mainstream research direction, and dozen...
PM2.5 is unanimously considered to be an important indicator of air quality. Sustained rainfall is a kind of typical but complex rainfall process in southern China with an uncertain duration and intervals. During sustained rainfall, the variation of...
As the world’s energy demand continues to expand, shale oil has a substantial influence on the global energy reserves. The third submember of the Mbr 3 of the Shahejie Fm, characterized by complicated mudrock lithofacies, is one of the signific...
The integration of graph embedding technology and collaborative filtering algorithms has shown promise in enhancing the performance of recommendation systems. However, existing integrated recommendation algorithms often suffer from feature bias and l...
Reciprocal recommendation requires satisfying preferences on both sides of a match, which differs from standard one-sided settings and often involves hierarchical structure (e.g., skills, seniority, education). We present biLorentzFM, which is a mult...