A Multitask Multiview Neural Network for End-to-End Aspect-Based Sentiment Analysis by Yong Bie, Yan Yang

“…The aspect-based sentiment analysis (ABSA) consists of two subtasks'aspect term extraction and aspect sentiment prediction. Existing methods deal with both subtasks one by one in a pipeline manner, in which there lies some problems in performance and real application. …”
Get full text

Power Quality Assessment and Optimization in FUZZY-Driven Healthcare Devices by Dinesh Kumar Nishad, Saifullah Khalid, Rashmi Singh

“…This paper introduces an innovative FUZZY-driven energy management system that combines convolutional neural networks (CNNs) for real-time power quality event detection, long short-term memory (LSTM) networks for predictive analytics, and reinforcement learning for optimized control. …”
Get full text

Location-assistant content distribution scheme for emergency rescue by Guomin Zhang, Lihua Song, Haitao Wang, Chao Hu, Na Wang

“…Due to the intermittent network connectivity and variety of emergency service, a content-classification-based publish/subscribe architecture and a GenericSpray routing algorithm based on the prediction of overlap opportunity in spatio-temporal positions are proposed. …”
Get full text

Multi-Index Monitoring and Evaluation on Rock Burst in Yangcheng Mine by Yunliang Tan, Yanchun Yin, Shitan Gu, Zhiwei Tian

“…Based on the foreboding information monitoring of the energy released in the developing process of rock burst, prediction system for rock burst can be established. …”
Get full text

Robust quantum spin liquid state in the presence of giant magnetic isotope effect in D3LiIr2O6 by T. Takayama, A. S. Gibbs, K. Kitagawa, Y. Matsumoto, K. Ishii, A. Kato, R. Takano, S. Bette, R. Dinnebier, H. Takagi

“…Nevertheless, the quantum liquid state is robust against the deuterium isotope exchange in contrast to the theoretical prediction that the Kitaev spin liquid is stable only for a limited phase space of magnetic interactions. …”
Get full text

A comparative study of interpolation methods for the development of ore distribution maps by Mahinaz M. Shawky

“…Geologists use deterministic and geostatistical methods as interpolation tools to generate a continuous (or prediction) ore distribution map from known sampled data. …”
Get full text

Long-Term Rainfall Information Forecast by Utilizing Constrained Amount of Observation through Artificial Neural Network Approach by Muhammed E. Akiner

“…The proposed technique is being used to estimate rainfall and make predictions regarding future precipitation. Bolu daily average rainfall by month data and a limited number of Düzce rainfall data were used. …”
Get full text

Influence of Natural Gas Hydrate’s Property Weakening from Dissociation on Subsidence of Seabed Sediments: A Simulation Study by Shuzhi Ma, Hongbo Li, Hongbiao Jia

“…A better understanding of the effect of soil mechanical weakening on seabed deformation will benefit the prediction and/or determination of geological conditions for safer hydrate production. …”
Get full text

Relieving popularity bias in recommendation via debiasing representation enhancement by Junsan Zhang, Sini Wu, Te Wang, Fengmei Ding, Jie Zhu

“…However, it lacks consideration of the significant disparity in popularity between items and may even introduce false negatives during the data augmentation, misleading user preference prediction. To address this issue, we combine contrastive learning with a weighted model for negative validation. …”
Get full text

Decomposition-Aware Framework for Probabilistic and Flexible Time Series Forecasting in Aerospace Electronic Systems by Yuanhong Mao, Xin Hu, Yulang Xu, Yilin Zhang, Yunan Li, Zixiang Lu, Qiguang Miao

“…Degradation prediction for aerospace electronic systems plays a crucial role in maintenance work. …”
Get full text

Analytical Steady-State Model for the Free Radical Solution Copolymerization of Acrylonitrile and Vinyl Acetate and Their Charge-Transfer Complex in a Continuous Stirred Tank React... by Oscar Meza-Díaz, Juan-Carlos Tapia-Picazo, Adrian Bonilla-Petriciolet, Gabriel Luna-Bárcenas, Daniel Alcalá-Sánchez, José-Enrique Jaime-Leal, Pedro-Jesús Herrera-Franco

“…The results of the predictions of the developed model were compared with the experimental data for validation. …”
Get full text

Daily allocation of energy consumption forecasting of a power distribution company using optimized least squares support vector machine by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Mohammad Bin Amin

“…The optimized LSSVM hyper-parameters, specifically the regularization parameter (γ) and the kernel parameter (σ2), were applied to test data to enhance accuracy guided by the Mean Absolute Prediction Error (MAPE), ensuring precise alignment of forecasted values with actual energy consumption data. …”
Get full text

Incorporating Machine Learning in Capture-Recapture Estimation of Survey Measurement Error by Maaike Walraad, Jonas Klingwort, Joep Burger

“…In particular, we study differences in prediction quality, point estimates, variance estimates, and estimates of measurement error in five years. …”
Get full text

Early identification of dropouts during the special forces selection program by Ruud J. R. den Hartigh, Rik Huijzer, Frank J. Blaauw, Age de Wit, Peter de Jonge

“…Additionally, we found that dropout could often be predicted multiple weeks in advance. These findings offer novel insights in the use of prediction models on psychological and physical processes, specifically in the context of special forces selection. …”
Get full text

A Software Tool for Optimal Sizing of PV Systems in Malaysia by Tamer Khatib, Azah Mohamed, K. Sopian

“…The ANN based model for metrological prediction uses four meteorological variables, namely, sun shine ratio, day number and location coordinates. …”
Get full text

Nonlinear Model of Vibrating Screen to Determine Permissible Spring Deterioration for Proper Separation by Cristian G. Rodriguez, Manuel A. Moncada, Emilio E. Dufeu, Mario I. Razeto

“…The proposed model allows the prediction of vibrating screen behavior when there is a reduction in spring stiffness. …”
Get full text

Static Mechanical Properties and Microscopic Analysis of Hybrid Fiber Reinforced Ultra-High Performance Concrete with Coarse Aggregate by Shengbing Liu, Yonglei Zhang

“…Finally, three kinds of strength parameters are predicted based on the back propagation (BP) neural network system. …”
Get full text

Tumor Size as a Critical Prognostic Factor in T1-2 Stage Esophageal Cancer by Zilong Wu, Bentong Yu

“…Tumor size has been measured in esophageal cancer for decades, but the role of tumor size in relation to T stage in the prediction of survival is still underappreciated. Thus, the present study is aimed at investigating the influence of T stage on the predictive value of tumor size in clinical stage I–IV esophageal cancer patients. …”
Get full text

Online energy consumption forecast for battery electric buses using a learning-free algebraic method by Zejiang Wang, Guanhao Xu, Ruixiao Sun, Anye Zhou, Adian Cook, Yuche Chen

“…Abstract Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. …”
Get full text

Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters by C. Braxton Owens, Nithin Mathew, Tyce W. Olaveson, Jacob P. Tavenner, Edward M. Kober, Garritt J. Tucker, Gus L. W. Hart, Eric R. Homer

“…Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. Key steps for property prediction common to grain boundaries and other variable-sized atom clustered structures include: (1) describing the atomic structure as a feature matrix, (2) transforming the variable-sized feature matrix to a fixed length common to all structures, and (3) applying a machine learning algorithm to predict properties from the transformed matrices. …”
Get full text