Uplift modeling is a machine learning technique that aims to model treatment effects heterogeneity. It has been used in business and health sectors to predict the effect of a specific action on a given individual. Despite its advantages, uplift models show high sensitivity to noise and disturbance, which leads to unreliable results. In this paper we show different approaches to address the prob...

In this work, a new control method for uncertain processes is developed based on two-degree-of-freedom control structure. The setpoint tracking controller designed by input/output linearization technique is used to regulate the disturbance-free output and the disturbance rejection controller designed is designed by high-gain technique. The advantage of two-degree-of-freedom control structure is...

Power quality (PQ) is becoming prevalent and of critical importance for power industry recently. The fast expansion in use of power electronics devices led to a wide diffusion of nonlinear, time-variant loads in the power distribution network, which cause massive serious power quality problems. The quantitative detection of two distortions of voltage waveform, i.e., voltage sag and voltage swel...

Previous research has stressed the relevance of nonacoustical factors in the perception of aircraft noise. However, it is largely empirically driven and lacks a sound theoretical basis. In this paper, a theoretical model which explains noise annoyance based on the psychological stress theory is empirically tested. The model is estimated by applying structural equation modeling based on data fro...

A new algorithm for power system disturbance classification is proposed in this paper. It is a two-stage system that employs the great potentials of the discrete wavelet transform (DWT), Kalman filter and a fuzzy-expert system. For the first stage, the captured voltage waveform is passed through the DWT to determine the noise inside it. The covariance of this noise is then calculated and fed to...

In a recent work by Betser and Zeheb, the modified adaptive output error algorithm for identification was proposed. In this paper, we prove that the solution is biased for most practical types of disturbance noise, including the white noise case. Bias can be avoided in certain cases, under the verification of a relation between the spectrum of the noise and the noise-free solution, specified in...

Noise annoyance is a feeling of displeasure or disturbance caused by noise. It is a sensitive indicator of adverse noise effects. Noise annoyance can only be partially explained by acoustical characteristics of noise – its level, frequency, duration, source etc. Non-acoustical factors, such as personal characterisitcs (age, gender, noise sensitivity), and social, residential or environmental fa...

The adaptive generalized predictive control (GPC), which combines the process of system identification using recursive least-squares (RLS) algorithm and the process of generalized predictive feedback control design, has been presented and successfully implemented on testbeds. In this paper, the adaptive GPC algorithm is extended when the disturbance measurement signal is available for feedforwa...

Sleep disturbance induced by night-time noise is a serious environmental problem that can cause adverse health effects, such as hypertension and ischemic heart disease. Night-time noise indices are used to facilitate the enforcement of permitted noise levels during night-time. However, existing night-time noise indices, such as sound exposure level (SEL), maximum sound level (LA max) and night ...