A mention may or may not be coreferred elsewhere in the document. Identifying those mentions that are corefered (called coreferents) is an important step in many NLP tasks, like coreference resolution. To classify a mention as singleton or coreferent using just one sentence is a challenging problem, but previous work suggests that there are cues in a sentence which can be used to predict if a m...

At present data transmission widely uses wireless network framework for transmitting large volume of data. It generates numerous security problems and privacy issues which laid a way developing IDS. IDS act as preventive technique in securing computer networks. Previously there are metaheuristic deep learning algorithms used detecting threats. Some affected by dynamic growth feature spaces othe...

• For the first time, automatic detection of heart failure (HF) from speech is studied. Both vocal tract and glottal source parameters are used in feature extraction. Four machine learning algorithms as classifiers. Applying Feature selection on + features improved classification accuracy. Among classifiers, neural network gave best performance. Heart a major global health concern increasing pr...

Artificial intelligence methods can remarkably reduce costs for water supply and sanitation systems help ensure compliance with the quality of drinking wastewater treatment. Therefore, modelling predicting to control pollution has been widely researched. The novelty proposed system is presented develop an efficient operation monitoring a sustainable friendly green environment. In this work, ada...

The higher share of renewable energy sources in the electrical grid and electrification significant sectors, such as transport heating, are imposing a tremendous challenge on operation system due to increase complexity, variability uncertainties associated with these changes. recent advances computational technologies ever-growing data availability allowed development sophisticated efficient al...

Abstract. Various machine learning methods were attempted in the global mapping of surface ocean partial pressure CO2 (pCO2) to reduce uncertainty sink estimate due undersampling pCO2. In previous research, predictors pCO2 usually selected empirically based on theoretic drivers pCO2, and same combination was applied all areas except where there a lack coverage. However, differences between diff...

Abstract Natural fractures play an essential role in the characterization and modeling of hydrocarbon reservoirs. Modeling fractured reservoirs requires understanding fracture characteristics. Fractured zones can be detected by using seismic data, petrophysical logs, well tests, drilling mud loss history core description. In this study, feed-forward neural networks (FFNN), cascade feed forward ...

Groundwater is an essential resource for drinking and agricultural purposes in the Al-Jouf region, Saudi Arabia. The main objective of this study to assess groundwater quality irrigation region. Physicochemical characteristics were determined, including total dissolved solids (TDS), pH, electric conductivity (EC), hardness, various anions cations. index (WQI) was calculated determine suitabilit...

We develop a new nonparametric method to reconstruct the Equation of State (EoS) Neutron Star with multimessenger data. As an universal function approximator, Feed-Forward Neural Network (FFNN) one hidden layer and sigmoidal activation can approximately fit any continuous function. Thus we are able implement FFNN representation EoSs. This is validated by its capabilities fitting theoretical EoS...