The coronavirus COVID-19 has recently started to spread rapidly in Malaysia. The number of total infected cases has increased to 3662 on 05 April 2020, leading to the country being placed under lockdown. As the main public concern is whether the current situation will continue for the next few months, this study aims to predict the epidemic peak using the Susceptible–Exposed–Infectious–Recovered (SEIR) model, with incorporation of the mortality cases. The infection rate was estimated using the Genetic Algorithm (GA), while the Adaptive Neuro-Fuzzy Inference System (ANFIS) model was used to provide short-time forecasting of the number of infected cases. The results show that the estimated infection rate is 0.228 ± 0.013, while the basic reproductive number is 2.28 ± 0.13. The epidemic peak of COVID-19 in Malaysia could be reached on 26 July 2020, with an uncertain period of 30 days (12 July–11 August). Possible interventions by the government to reduce the infection rate by 25% over two or three months would delay the epidemic peak by 30 and 46 days, respectively. The forecasting results using the ANFIS model show a low Normalized Root Mean Square Error (NRMSE) of 0.041; a low Mean Absolute Percentage Error (MAPE) of 2.45%; and a high coefficient of determination (R2) of 0.9964. The results also show that an intervention has a great effect on delaying the epidemic peak and a longer intervention period would reduce the epidemic size at the peak. The study provides important information for public health providers and the government to control the COVID-19 epidemic.

No abstract

In active noise control (ANC) applications, the saturation effect of the loudspeaker in the secondary path is considered as the most serious problem that could degrade performance of standard filtered-x least mean square (FXLMS) control algorithm. When the loudspeaker exhibits nonlinearities, the linear modeling approach fails to identify the secondary path accurately. In the literature, the nonlinear FXLMS (NLFXLMS) algorithm has been proposed to update the ANC controller with a blockoriented secondary path model. This model consists of nonlinear and linear filters whereby the nonlinear part which represents the saturation effect of the amplifier-loudspeaker system is modeled by a scaled error function (SEF). The NLFXLMS algorithm requires an exact copy of the linear and nonlinear models of the secondary path. However, NLFXLMS cannot be implemented in real time because the modeling of the SEF cannot be realized. In this paper, a new method to model the secondary path using the Hammerstein model structure and tangential hyperbolic function (THF) is proposed. The THF can represent the SEF to a certain degree of accuracy. Furthermore, the modeling of the THF can be realized using least mean square (LMS) algorithm and utilized in the NLFXLMS control scheme. Simulation results show that the performance of the THF-based NLFXLMS algorithm is comparable with the SEF-based NLFXLMS.

Tissue recovery is important in preventing tissue deterioration, which is induced by pressure and may lead to pressure ulcers (PU). Reactive hyperaemia (RH) is an indicator used to identify people at risk of PU. In this study, the effect of different recovery times on RH trend is investigated during repetitive loading. Twenty-one male Sprague-Dawley rats (seven per group), with body weight of 385-485 g, were categorised into three groups and subjected to different recovery times with three repetitive loading cycles. The first, second, and third groups were subjected to short (3 min), moderate (10 min), and prolonged (40 min) recovery, respectively, while fixed loading time and pressure (10 min and 50 mmHg, respectively). Peak hyperaemia was measured in the three cycles to determine trends associated with different recovery times. Three RH trends (increasing, decreasing, and inconsistent) were observed. As the recovery time is increased (3 min vs. 10 min vs. 40 min), the number of samples with increasing RH trend decreases (57% vs. 29% vs. 14%) and the number of samples with inconsistent RH trend increases (29% vs. 57% vs. 72%). All groups consists of one sample with decreasing RH trend (14%). Results confirm that different recovery times affect the RH trend during repetitive loading. The RH trend may be used to determine the sufficient recovery time of an individual to avoid PU development.

This paper presents the development of minimum effort active noise control theory for feedforward single-input single output (SISO) architecture, which includes the feedback acoustic path in the controller formulation. The theoretical range of effective minimum effort parameter with respect to level of point cancellation at the observer and the interference pattern generated around the observer for periodic noise control in free-field are investigated. It is found that for a minimum of 6 dB cancellation which corresponds to cancellation factor of 0.75 at the observer, the effort parameter must be specified as less than unity. It is also found that the cancellation pattern characterised by 20 dB, 10 dB and 6 dB zones reduces significantly in terms of size with an increase in the value of the effort term.