Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm

A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. The DE at the upper level is formulated as combinatorial optimization to search for the network architecture while the associated network weights that minimize the prediction error is provided by the GA at the lower level. The performance of the algorithm is evaluated on identification of a laboratory rotary motion system. The system identification results show the effectiveness of the proposed algorithm for nonparametric model development

Detection of vascular intersection in retina fundus image using modified cross point number and neural network technique

Vascular intersection can be used as one of the symptoms for monitoring and diagnosis of diabetic retinopathy from fundus images. In this work we apply the knowledge of digital image processing, fuzzy logic and neural network technique to detect bifurcation and vein-artery cross-over points in fundus images. The acquired images undergo preprocessing stage for illumination equalization and noise removal. Segmentation stage clusters the image into two distinct classes by the use of fuzzy c-means technique, neural network technique and modified cross-point number (MCN) methods were employed for the detection of bifurcation and cross-over points. MCN uses a 5x5 window with 16 neighboring pixels for efficient detection of bifurcation and cross over points in fundus images. Result obtained from applying this hybrid method on both real and simulated vascular points shows that this method perform better than the existing simple cross-point number (SCN) method, thus an improvement to the vascular point detection and a good tool in the monitoring and diagnosis of diabetic retinopathy

Multisite spectroscopic seismic study of the beta Cep star V2052 Oph: inhibition of mixing by its magnetic field

We used extensive ground-based multisite and archival spectroscopy to derive observational constraints for a seismic modelling of the magnetic beta Cep star V2052 Ophiuchi. The line-profile variability is dominated by a radial mode (f_1=7.14846 d^{-1}) and by rotational modulation (P_rot=3.638833 d). Two non-radial low-amplitude modes (f_2=7.75603 d^{-1} and f_3=6.82308 d^{-1}) are also detected. The four periodicities that we found are the same as the ones discovered from a companion multisite photometric campaign (Handler et al. 2012) and known in the literature. Using the photometric constraints on the degrees l of the pulsation modes, we show that both f_2 and f_3 are prograde modes with (l,m)=(4,2) or (4,3). These results allowed us to deduce ranges for the mass (M \in [8.2,9.6] M_o) and central hydrogen abundance (X_c \in [0.25,0.32]) of V2052 Oph, to identify the radial orders n_1=1, n_2=-3 and n_3=-2, and to derive an equatorial rotation velocity v_eq \in [71,75] km s^{-1}. The model parameters are in full agreement with the effective temperature and surface gravity deduced from spectroscopy. Only models with no or mild core overshooting (alpha_ov \in [0,0.15] local pressure scale heights) can account for the observed properties. Such a low overshooting is opposite to our previous modelling results for the non-magnetic beta Cep star theta Oph having very similar parameters, except for a slower surface rotation rate. We discuss whether this result can be explained by the presence of a magnetic field in V2052 Oph that inhibits mixing in its interior.Comment: 12 pages, 6 figures and 5 tables; accepted for publication in MNRAS on 2012 August 1

A review of combined advanced oxidation technologies for the removal of organic pollutants from water

Water pollution through natural and anthropogenic activities has become a global problem causing short-and long-term impact on human and ecosystems. Substantial quantity of individual or mixtures of organic pollutants enter the surface water via point and nonpoint sources and thus affect the quality of freshwater. These pollutants are known to be toxic and difficult to remove by mere biological treatment. To date, most researches on the removal of organic pollutants from wastewater were based on the exploitation of individual treatment process. This single-treatment technology has inherent challenges and shortcomings with respect to efficiency and economics. Thus, application of two advanced treatment technologies characterized with high efficiency with respect to removal of primary and disinfection by-products in wastewater is desirable. This review article focuses on the application of integrated technologies such as electrohydraulic discharge with heterogeneous photocatalysts or sonophotocatalysis to remove target pollutants. The information gathered from more than 100 published articles, mostly laboratories studies, shows that process integration effectively remove and degrade recalcitrant toxic contaminants in wastewater better than single-technology processing. This review recommends an improvement on this technology (integrated electrohydraulic discharge with heterogeneous photocatalysts) viz-a-vis cost reduction in order to make it accessible and available in the rural and semi-urban settlement. Further recommendation includes development of an economic model to establish the cost implications of the combined technology. Proper monitoring, enforcement of the existing environmental regulations, and upgrading of current wastewater treatment plants with additional treatment steps such as photocatalysis and ozonation will greatly assist in the removal of environmental toxicants

Will Africans take COVID-19 vaccination?

The economic and humanistic impact of COVID-19 pandemic is enormous globally. No definitive treatment exists, hence accelerated development and approval of COVID-19 vaccines, offers a unique opportunity for COVID-19 prevention and control. Vaccine hesitancy may limit the success of vaccine distribution in Africa, therefore we assessed the potentials for coronavirus vaccine hesitancy and its determinants among Africans. An online crosssectional African-wide survey was administered in Arabic, English, and French languages. Questions on demographics, self-reported health status, vaccine literacy, knowledge and perception on vaccines, past experience, behavior, infection risk, willingness to receive and affordability of the SARS-COV-2 vaccine were asked. Data were subjected to descriptive and inferential statistics. A total of 5,416 individuals completed the survey. Approximately, 94% were residents of 34 African countries while the other Africans live in the Diaspora. Only 63% of all participants surveyed were willing to receive the COVID-19 vaccination as soon as possible and 79% were worried about its side effects. Thirty-nine percent expressed concerns of vaccine-associated infection. The odds of vaccine hesitancy was 0.28 (95% CI: 0.22, 0.30) among those who believed their risk of infection was very high, compared to those who believed otherwise. The odds of vaccine hesitancy was one-fifth (OR = 0.21, 95% CI: 0.16, 0.28) among those who believed their risk of falling sick was very high, compared to those who believed their risk of falling very sick was very low. The OR of vaccine hesitancy was 2.72 (95% CI: 2.24, 3.31) among those who have previously refused a vaccine for themselves or their child compared to counterparts with no self-reported history of vaccine hesitancy. Participants want the vaccines to be mandatory (40%), provided free of charge (78%) and distributed in homes and offices (44%). COVID-19 vaccine hesitancy is substantial among Africans based on perceived risk of coronavirus infection and past experiences.http://www.plosone.orgam2022Veterinary Tropical Disease

Will Africans take COVID-19 vaccination?

The economic and humanistic impact of COVID-19 pandemic is enormous globally. No definitive treatment exists, hence accelerated development and approval of COVID-19 vaccines, offers a unique opportunity for COVID-19 prevention and control. Vaccine hesitancy may limit the success of vaccine distribution in Africa, therefore we assessed the potentials for coronavirus vaccine hesitancy and its determinants among Africans. An online cross-sectional African-wide survey was administered in Arabic, English, and French languages. Questions on demographics, self-reported health status, vaccine literacy, knowledge and perception on vaccines, past experience, behavior, infection risk, willingness to receive and affordability of the SARS-COV-2 vaccine were asked. Data were subjected to descriptive and inferential statistics. A total of 5,416 individuals completed the survey. Approximately, 94% were residents of 34 African countries while the other Africans live in the Diaspora. Only 63% of all participants surveyed were willing to receive the COVID-19 vaccination as soon as possible and 79% were worried about its side effects. Thirty-nine percent expressed concerns of vaccine-associated infection. The odds of vaccine hesitancy was 0.28 (95% CI: 0.22, 0.30) among those who believed their risk of infection was very high, compared to those who believed otherwise. The odds of vaccine hesitancy was one-fifth (OR = 0.21, 95% CI: 0.16, 0.28) among those who believed their risk of falling sick was very high, compared to those who believed their risk of falling very sick was very low. The OR of vaccine hesitancy was 2.72 (95% CI: 2.24, 3.31) among those who have previously refused a vaccine for themselves or their child compared to counterparts with no self-reported history of vaccine hesitancy. Participants want the vaccines to be mandatory (40%), provided free of charge (78%) and distributed in homes and offices (44%). COVID-19 vaccine hesitancy is substantial among Africans based on perceived risk of coronavirus infection and past experiences

Control of an inverted pendulum using MODE-based optimized LQR controller

This paper presents an evolutionary optimization based LQR controller design for an inverted pendulum system. The objective is to address the challenges of appropriate design parameters selection in LQR controller while providing optimal performance compromise between the system control objectives with respect to pendulum angle and position response. Hence, a Multiobjective differential evolution algorithm is proposed to design an LQR controller with optimal compromise between the conflicting control objectives. The performance of the MODEbased LQR is benchmarked with an existing controller from the system manufacturer (QANSER). The performance shows the effectiveness of the proposed design algorithm, and in addition provides an efficient solution to conventional trial and error design approach

Robust state feedback control design via PSO-based constrained optimisation

Computational intelligence has been successfully applied to many engineering applications including control engineering problems. In this paper, a robust state feedback control design using particle swarm optimizer based constrained optimization is proposed. The feedback controller is optimized based on state space model of the plant with structured uncertainty such that the closed-loop system would have maximum stability radius. A wedge region is assigned as a constraint to locate the desired closed-loop poles, which correspond to time-domain control system performance. The proposed controller design is applied to anti-swing control for a gantry crane system. The experimental result is shown, and comparison with that of conventional linear quadratic regulator based controller and H∞ loop shaping controller are made. The proposed method achieves a satisfactory robust performance based on the structured singular value analysis and the experimental results

Optimization of PID controller for flexible link system using a pareto-based multi-objective differential (PMODE) evolution

The conflict between the transient performance of the link position and tip vibration in a flexible link system has made the control of such system a challenging task. The system is required to obtain a fast transient position response together with minimal tip vibration. This can be viewed like many other reallife control problems as a multi-objectives optimization problem in which an optimal compromise between the design objectives is required. PID controller is noted with historical simplicity in terms of design and implementation when compares to other linear time invariant (LTI) control techniques. However, the shortcoming of PID lies in the tuning of the controller gains for a given problem. To overcome this, a Multiobjective Differential Evolution (MODE)-based PID controller is reported in this study for controlling a flexible link system. The gains of the PID controller are tuned using a developed MATLAB-based MODE to obtain pareto-solutions for both link position and tip vibration. The performance of the selected best PID controller from MODE-based design is benchmarked with the LQR controller provided by the manufacturer (QUANSER) of the laboratory scale flexible link plant. Though, the LQR shows better transient performance in the position responses, the developed MODE-PID gave better tip response performances as indicated in both the simulation and experimental responses obtaine