Sentiment analysis of tweets has attracted considerable attention recently for potential use in commercial and public sector applications. Typical sentiment analysis classifies the sentiment of sentences into several discrete classes (e.g., positive and negative). The aim of Task 4 subtask C of SemEval-2016 is to classify the sentiment of tweets into an ordinal five-point scale. In this paper, ...

Real time and spatially distributed Ta (air temperature) data are desired for many applications. Ts (land surface temperature) derived from remote sensors has been used to estimate Ta in previous studies. Exploring MODIS Aqua Ts and station measured daily maximum and minimum Ta over east Africa, we found that Ts did not agree well with Ta during the day (MAE (Mean Absolute Error) = 6.9 ± 5.0 ◦C...

Predicted electricity consumption is needed to perform energy management. Electricity prediction also very important in the development of intelligent power grids and advanced electrification network information. we implement a Support Vector Machine (SVM) predict electrical loads results compared measurable loads. Laboratory have their own characteristics when residential, commercial, or indus...

Platinum containing compounds are promising antitumor agents, but must enter cells before reaching their main biological target, namely DNA. Their distribution within the body, and hence their activity is to a large extent determined by their lipophilicity, thus there is a strong interest to develop computational methods to predict this important property. This study analyses accuracy of five m...

The use of land surface temperature and vertical temperature profile data from Moderate Resolution Imaging Spectroradiometer (MODIS), to estimate high spatial resolution daily and monthly maximum and minimum 2 m above ground level (AGL) air temperatures for regions with limited in situ data was investigated. A diurnal air temperature change model was proposed to consider the differences between...

This paper analyzes the validity of temperature maps obtained by means of single and mixed interpolation methods. In this context, several interpolation methods are used for the temperature mapping: inverse distance square (IDS), ordinary kriging (OK) and co-kriging (CK) and mixed methods (combined global, local and geostatistical methods). And the validity of the maps is checked through the cr...

The paper presents the application of support vector regression (SVR) to accurate forecasting of the tangential displacement of a concrete dam. The SVR nonlinear autoregressive model with exogenous inputs (NARX) was developed and tested using experimental data collected during fourteen years. A total of 573 data were used for training of the SVR model whereas the remaining 156 data were used to...

OBJECTIVE Clinicians often overestimate the probability of a disease given a positive test result (positive predictive value; PPV) and the probability of no disease given a negative test result (negative predictive value; NPV). The purpose of this study was to investigate whether experiencing simulated patient cases (ie, an 'experience format') would promote more accurate PPV and NPV estimates ...

The growing importance and utilization of measuring brain waves (e.g. EEG signals of eye state) in brain computer interface (BCI) applications highlighted the need for suitable classification methods. In this paper, a comparison between three of wellknown classification methods (i.e. support vector machine (SVM), hidden Markov map (HMM), and radial basis function (RBF)) for EEG based eye state ...

In the present work, we propose a scheme for the fusion of different phone duration models, operating in parallel. Specifically, the predictions from a group of dissimilar and independent to each other individual duration models are fed to a machine learning algorithm, which reconciles and fuses the outputs of the individual models, yielding more precise phone duration predictions. The performa...