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A resource administrator (RM) can distribute tasks processing time between heterogeneous processors is presented. Its design is based on analyzing of the possible forms of attention to pending tasks and in the previous knowledge about them. A model is proposed based on difference equations that quantify the resource allocation of each task and choose the best processor where the task can be executed. The scheme adapts to dynamic changes in the requirements or the number of tasks. [ABSTRACT FROM AUTHOR]

The aim in this paper is experimentally to show that a predictive pulsed control law is able to enlarge the stabilizing sampling periods of a networked control system (NCS) more than the classical predictive ZOH-control law. Additionally, using a comparisson in the system response between the predictive pulsed control law and the predictive ZOH-control law, it is obtained that the pulsed control law requires less energy consumption to stabilize a NCS exposed to large time-delays. A 3-DOF Hover is used as case study. [ABSTRACT FROM AUTHOR]

At present, network control systems employ a common approximation to solve the connectivity issue due to time delays coupled with external factors . However, this approach tends to be complex in terms of time delays, and the inherent local phase is missing. Therefore, it is necessary to study the behavior of the delays as well as the integration of the differential equations of these bounded delays. The related time delays need to be known a priori, but from a dynamic real-time perspective in order to understand the dynamic phase behavior. The objective of this paper is to demonstrate the inclusion of the data frequency transmission and time delays that are bounded as parameters of the dynamic response from a real-time scheduling approximation, considering the local phase situation. The related control law is designed considering a fuzzy logic approximation for nonlinear time delays coupling. The main advantage is the integration of this behavior through extended state space representation. This keeps certain linear and bounded behavior leading to a stable situation during an events presentation, based on an accurate data transmission rate. An expected result is that the basics of the local phase missing as a result of the local bounded time delays from the lack of tide synchronization conforms to the modeling approximation. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy controller for class of non-linear networked control systems; the varying time delays and packet loss are taken as a variable sampling period of the system. The variable sampling period is estimated using a time stamped and probability density function. A fuzzy model smoothly switches to estimate the system state; the antecedent input is the estimated sampling period and the consequent part is formed by linear models discretized with specific sampling periods. The fuzzy controller generates a control input using the estimated states to ensure system stability for a wide range of sampling periods. A two-degree-of-freedom helicopter is used to show the applicability and effectiveness of the controller with robustness to traffic. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy control approach to a helicopter MIMO nonlinear system, implemented on a Networked Control System, as case study. For this, a hardware-in-the-Loop implementation is developed using several multi-channel A/D Cards, integrated to a computer network system. Variant time delays are considered over Ethernet and CANBUS networks. Fuzzy logic is used to deal with the complexity of the integrated computer network as well as with the dynamics of the system. Two fuzzy logic control systems are coupled for both signals of the helicopter case study: yaw and pitch. Both these tend to concentrate around desired references, considering variant time delays. [ABSTRACT FROM AUTHOR]

Nowadays the study of faults and their consequences becomes an issue into highly safety critical computer network systems. How to bound the effects of a fault and how to tackle them into a dynamic system is still an open field. In here an approach to tackle this problem is presented. The use of Takagi-Sugeno fuzzy logic structure is given in order to accomplish two challenges, the presence of local faults and the respective time delays within a realtime distributed system. This approach is pursued as reconfigurable strategy according to communication time delays within a real-time distributed system. This approach is pursued as reconfigurable strategy according to communication delays. [ABSTRACT FROM AUTHOR]

Fault diagnosis currently offers different alternatives to classify faults at early stages, such as model-based and knowledge-based techniques. Nevertheless, fault classification for time-varying systems is still an open problem. Strategies such as self-organizing maps and principal component analysis ensure fault classification to bounded time-variance faults. The approach presented in this paper proposes the use of three non-supervised neural networks. The first two networks overlapped by certain time shift. The third network performs a comparison between the two networks outputs in the previous stage. As a result, the system classifies the fault even if the system is time-variant. The strategy named as Overlapped ART2A Network, aims to obtain an autonomous performance and on-line fault classification. Results show the effectiveness of the approach considering a case study with fault and fault-free scenarios. [ABSTRACT FROM AUTHOR]

Online reconfiguration performed by a computer network system needs to be addressed from several perspectives due to complexity onto the system. This paper proposes different modeling approximations to obtain a holistic view of reconfiguration onto complex systems. First model is dynamic system modeling, second is an automaton in order to bound possible scenarios and third model is a Real Time scheduling algorithm to match possible configurations and related control laws. [ABSTRACT FROM AUTHOR]

Background: We compared the probability of hospitalization and death caused by COVID-19 in patients with comorbidities during three periods defined for this study: first-wave (FW), interwave period (IP), and second-wave (SW) observed in Mexico City., Methods: In this registry-based study, we included individuals over 20 years of age. During the FW (symptomatic), the IP, and the SW (symptomatic and asymptomatic), participants were diagnosed using nasopharyngeal swabs. Symptomatic individuals with risk factors for serious disease or death were referred to the hospital. SARS-CoV-2 infection was defined by RT-qPCR in all hospitalized patients. All data were added to the SISVER database. Bayesian analysis and False Discovery Rate were used for further evaluation., Results: The study included 2 260 156 persons (mean age of 43.1 years). Of these, 8.6% suffered from DM, 11.6% arterial hypertension, and 9.7% obesity. Of the total, 666 694 persons tested positive (29.5%). Of the infected persons, a total of 85 587 (12.8%) were hospitalized: 24 023 in the FW; 16 935 in the IP, and 44 629 in the SW. Of the hospitalized patients, there were 42 979 deaths (50.2%), in the FW, 11 964 (49.8%), in the IP, 6794 (40.1%), and in the SW 24 221 (54.3%). The probability of death among individuals hospitalized with or without comorbidities increased consistently in all age groups. A significant increase in the Fatality Rate was observed in individuals with comorbidities (1.36E-19< = FDR< = 3.36E-2). A similar trend was also observed in individuals without comorbidities (1.03E-44< = FDR< = 5.58E-4)., Conclusions: The data from this study show a considerable increase in the number of detected cases of infection between the FW and SW. In addition, 12.8% of those infected were hospitalized for severe COVID-19. A high mortality rate was observed among hospitalized patients (>50%). An age-dependent probability of death was observed with a positive trend in hospitalized patients with and without comorbidities., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no conflicts of interest., (Copyright © 2022 by the Journal of Global Health. All rights reserved.)

Background: The COVID-19 pandemic has caused an exponential increase in the demand for medical care worldwide. In Mexico, the COVID Medical Units (CMUs) conversion strategy was implemented., Objective: To evaluate the CMU coverage strategy in the Mexico City Metropolitan Area (MCMA) by territory., Materials: The CMU directory was used, as were COVID-19 infection and mobility statistics and Mexican 2020 census information at the urban geographic area scale. The degree of urban marginalization by geographic area was also considered., Method: Using descriptive statistics and the calculation of a CMU accessibility index, population aggregates were counted based on coverage radii. In addition, two regression models are proposed to explain (1) the territorial and temporal trend of COVID-19 infections in the MCMA and (2) the mobility of the COVID-infected population visiting medical units., Results: The findings of the evaluation of the CMU strategy were (1) in the MCMA, COVID-19 followed a pattern of contagion from the urban center to the periphery; (2) given the growth in the number of cases and the overload of medical units, the population traveled greater distances to seek medical care; (3) after the CMU strategy was evaluated at the territory level, it was found that 9 out of 10 inhabitants had a CMU located approximately 7 km away; and (4) at the metropolitan level, the lowest level of accessibility to the CMU was recorded for the population with the highest levels of marginalization, i.e., those residing in the urban periphery.

This paper presents a parallel implementation based on insight segmentation and registration toolkit for a multiscale feature extraction and region growing algorithm, applied to retinal blood vessels segmentation. This implementation is capable of achieving an accuracy (Ac) comparable to its serial counterpart (about 92%), but 8 to 10 times faster. In this paper, the Ac of this parallel implementation is evaluated by comparison with expert manual segmentation (obtained from public databases). On the other hand, its performance is compared with previous published serial implementations. Both these characteristics make this parallel implementation feasible for the analysis of a larger amount of high-resolution retinal images, achieving a faster and high-quality segmentation of retinal blood vessels.