Wind turbine technology is pursuing the maturation using advanced multi-megawatt machinery equipped by powerful monitoring systems. In this work, a multichannel convolutional neural network is employed to develop an autonomous databased fault diagnosis algorithm. This algorithm has been evaluated in a 5MW wind turbine benchmark model. Several faults for various wind speeds are simulated in the benchmark model, and output data are recorded. A multichannel convolutional neural network with multiple parallel local heads is utilized in order to consider changes in every measured variable separately to identify subsystem faults. selleck chemical Time-domain signals obtained from the wind turbine are portrayed as images and fed independently to the proposed network. Results show that the multivariable fault diagnosis scheme diagnoses the most common wind turbine faults and achieves high accuracy.This paper investigates the second-order bipartite consensus (BC) problems for networked robotic systems (NRSs) subject to model uncertainties and external disturbances over signed directed graphs. We have newly presented two classes of hierarchical control algorithms (HCAs) to solve the BC problems for NRSs in a more practical and challenging case of quantized-data interactions (QDIs) and time-varying transmission delays (TVTDs). By using Hurwitz criterion and Lyapunov stability argument, several sufficient conditions on control parameters are obtained and the BC performance of the regulated system is analyzed. Three examples validate the presented theoretical findings.Reversible watermarking is an active research area in the field of data security. In this manuscript, a reversible watermarking scheme able for electronic patient record (EPR) transmission and medical image authentication is introduced. The proposed scheme computes an adaptive authentication code from the image to be watermarked. Further, the watermark (authentication code and EPR) are embedded into the medical image through a novel image scaling up operation. While scaling up an original image with M×M pixels by a factor of 2, 3M2 number of pixel intensity values in the scaled-up image needs to be approximated by considering the original pixel values. In this work, a set of rules is defined to insert authentication code and EPR data through the copying of neighborhood pixels as the missing pixel intensity values in the new scaled-up image. When the neighborhood pixels have the same intensity value, the adaptive pixel copy operation will not be successful to insert the watermark. In such cases, the bit in the least significant position uses for the watermarking process. The standard medical images downloaded OsriX dataset is used for experimental study. The results obtained show that the new scheme introduced in this manuscript surpasses the existing reversible watermarking. The scheme introduced in this paper can be used as part of an automated system where EPR data needs to be transmitted along with the medical images for better healthcare services.In real industrial processes, new process "excitation" patterns that largely deviate from previously collected training data will appear due to disturbances caused by process inputs. To reduce model mismatch, it is important for a data-driven process model to adapt to new process "excitation" patterns. Although efforts have been devoted to developing adaptive process models to deal with this problem, few studies have attempted to develop an adaptive process model that can incrementally learn new process "excitation" patterns without performance degradation on old patterns. In this study, efforts are devoted to enabling data-driven process models with incremental learning ability. First, a novel incremental learning method is proposed for process model updating. Second, an adaptive neural network process model is developed based on the novel incremental learning method. Third, a nonlinear model predictive control based on the adaptive process model is implemented and applied for flotation reagent control. Experiments based on historical data provide evidence that the newly developed adaptive process model can accommodate new process "excitation" patterns and preserve its performance on old patterns. Furthermore, industry experiments carried out in a real-world lead-zinc froth flotation plant provide industrial evidence and show that the newly designed controller is promising for practical flotation reagent control.The problem of event-triggered prescribed performance control for a class of uncertain nonlinear systems with unknown control directions and faults is investigated. Compared with the existing methods, a new set of error transformation functions is defined for the first time. Although no approximate structure is adopted, prescribed performance control (PPC) and event triggered control (ETC) are realized simultaneously for the nonlinear system considered in this paper for the first time. The proposed control scheme can guarantee that all closed-loop signals are bounded, and the tracking error, as well as all state errors, converges within the adjustable constraint functions. Finally, two simulation experiments verify the effectiveness of the proposed algorithm.Johne's disease is chronic, incurable disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP). Most studies in Egypt focused on incidence of the disease in cattle but few studies were reported presence of antibodies against MAP in sheep. The present study determined the seroprevalence rate of MAP among sheep in four Governorates and assessed the associated risk factors to MAP-infection. The seroprevalence rate of MAP among sheep was non-significant varied between different Governorates, it was ranged between 3.75%-12.3%. The results revealed that the seroprevalence rate of the disease was significantly increased in diarrheic sheep (11 %, 95 %CI 7.2-16.2) during spring (15 %, 95 %CI 8.3-25) and summer (8%, 95 %CI 4.13-13.8) seasons. Contrary, the age of sheep and contact with other ruminants like cattle or goats had non-significant effect of spreading of MAP-infection among sheep. The detection of MAP in feces of sheep was carried out using culture and PCR to determine the efficiency of both tests.