Digital welding machine (DWM) is an advanced tool for material forming. The lifespan and health status of DWMs are closely related to the safety reliability. To address problem low accuracy in prediction DWMs, a model based on immune algorithm (IA) long short-term memory network (LSTM) with attention mechanism proposed. First, degradation characteristic indicators evaluated selected. Then, inde...

objectives microscopy of giemsa-stained thick and thin peripheral blood smear (pbs) remains as the standard laboratory method for the diagnosis of symptomatic malaria. this study was done to compare pbs with polymerase chain reaction (pcr) method for detecting asymptomatic malaria parasitemia. patients and method blood samples were collected from 900 asymptomatic school children between 7-11 ye...

capital asset pricing model (capm) has been among the common models to estimate expected returns rate. since the linearity assumption is considered in the standard version of the capital asset pricing model, estimating beta in nonlinear setting will be inconsistent and bias-oriented. therefore, this study tries to evaluate predictive power of nonlinear capital asset pricing model as well as sta...

Predictive models are increasingly deployed for the purpose of determining access to services such as credit, insurance, and employment. Despite potential gains in productivity and efficiency, several potential problems have yet to be addressed, particularly the potential for unintentional discrimination. We present an iterative procedure, based on orthogonal projection of input attributes, for...

As organizations gain awareness of the potential business value locked in their process execution event logs, “evidence-based” business process management (BPM) becomes a common tool for process analysts. In contrast to traditional process monitoring techniques which are typically performed using data from running process instances only, predictive evidence-based BPM methods tap also into histo...

Linear regression is commonly used in the audio industry to create objective measurement models that predict subjective data. For any model development, the measure used to evaluate the accuracy of the prediction is important. The most common measures assume a linear relationship between the subjective data and the prediction, though in the early stages of model development this is not always t...

In this work we directly incorporate user personality profiles into the task of matrix factorization for predicting user ratings. Unlike previous work using personality in recommender systems, we use only the presence of written reviews by users. Other work that incorporates text directly into the recommendation framework focuses primarily on insights into products/categories, potentially disre...