Several theories have been proposed to account for the medial frontal activity that is elicited during the evaluation of outcomes. Respectively, these theories claim that the medial frontal response reflects (i) the absolute deviation between the value of an outcome and its expected value (i.e. an absolute prediction error); (ii) the deviation between actual and expected outcomes, with a specif...

This paper introduces Mainiway AI Labs submitted system for the IJCNLP 2017 shared task on Dimensional Sentiment Analysis of Chinese Phrases (DSAP), and related experiments. Our approach consists of deep neural networks with various architectures, and our best system is a voted ensemble of networks. We achieve a Mean Absolute Error of 0.64 in valence prediction and 0.68 in arousal prediction on...

Short-term traffic flow prediction has long been regarded as a critical concern for intelligent transportation systems. On the basis of many existing prediction models, each having good performance only in a particular period, an improved approach is to combine these single predictors together for prediction in a span of periods. In this paper, a neural network model is introduced that combines...

Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented bl...

This paper introduces Mainiway AI Labs submitted system for the IJCNLP 2017 shared task on Dimensional Sentiment Analysis of Chinese Phrases (DSAP), and related experiments. Our approach consists of deep neural networks with various architectures, and our best system is a voted ensemble of networks. We achieve a Mean Absolute Error of 0.64 in valence prediction and 0.68 in arousal prediction on...

INTRODUCTION The pharmacokinetics of vancomycin are highly variable among neonates, which makes dosing challenging in this population. However, adequate drug exposure is critical, especially when treating methicillin-resistant Staphylococcus aureus (MRSA) infections. Utilization of population pharmacokinetic models and Bayesian methods offers the potential for developing individualized therapeu...

PURPOSE Dose-related toxicity of cyclophosphamide may be reduced and therapeutic efficacy may be improved by pharmacokinetic sampling and dose adjustment to achieve a target area under the curve (AUC) for two of its metabolites, hydroxycyclophosphamide (HCY) and carboxyethylphosphoramide mustard (CEPM). To facilitate real-time dose adjustment, we developed open-source code within the statistica...

the vast use of linear prediction coefficients (lpc) in speech processing systems has intensified the importance of their accurate computation. this paper is concerned with computing lpc coefficients using evolutionary algorithms: genetic algorithm (ga), particle swarm optimization (pso), dif-ferential evolution (de) and particle swarm optimization with differentially perturbed velocity (pso-dv...

Air ticket sales revenue is an important source of revenue for travel agencies, and if future air ticket sales revenue can be accurately forecast, travel agencies will be able to advance procurement to achieve a sufficient amount of cost-effective tickets. Therefore, this study applied the Artificial Neural Network (ANN) and Genetic Algorithms (GA) to establish a prediction model of travel agen...