Diagnóstico da atuação de institutos para pesquisas e prestação de serviços / Performance diagnosis of institutes for research and services

2021 ◽  
Vol 7 (7) ◽  
pp. 73125-73141
Author(s):  
Wendell Soares Pacheco ◽  
Ligia Maria Soto Urbina ◽  
José Ribamar Oliveira Cavalcante Junior ◽  
Pedro Pessoa Mendes ◽  
Mischel Carmen Neyra Belderrain ◽  
...  
2017 ◽  
Vol 123 ◽  
pp. S709
Author(s):  
P.M. Samper Ots ◽  
A. Luis Cardo ◽  
M.A. Cabeza Rodriguez ◽  
C. Vallejo Ocaña ◽  
L.A. Glaria Enriquez ◽  
...  

2015 ◽  
Vol 40 (9) ◽  
pp. 918-923 ◽  
Author(s):  
Kelly de Jesus ◽  
Ana Sousa ◽  
Karla de Jesus ◽  
João Ribeiro ◽  
Leandro Machado ◽  
...  

Swimming and training are carried out with wide variability in distances and intensities. However, oxygen uptake kinetics for the intensities seen in swimming has not been reported. The purpose of this study was to assess and compare the oxygen uptake kinetics throughout low-moderate to severe intensities during incremental swimming exercise. We hypothesized that the oxygen uptake kinetic parameters would be affected by swimming intensity. Twenty male trained swimmers completed an incremental protocol of seven 200-m crawl swims to exhaustion (0.05 m·s−1 increments and 30-s intervals). Oxygen uptake was continuously measured by a portable gas analyzer connected to a respiratory snorkel and valve system. Oxygen uptake kinetics was assessed using a double exponential regression model that yielded both fast and slow components of the response of oxygen uptake to exercise. From low-moderate to severe swimming intensities changes occurred for the first and second oxygen uptake amplitudes (P ≤ 0.04), time constants (P = 0.01), and time delays (P ≤ 0.02). At the heavy and severe intensities, a notable oxygen uptake slow component (>255 mL·min−1) occurred in all swimmers. Oxygen uptake kinetics whilst swimming at different intensities offers relevant information regarding cardiorespiratory and metabolic stress that might be useful for appropriate performance diagnosis and training prescription.


2021 ◽  
Vol 58 (1) ◽  
pp. 3109-3120
Author(s):  
Mehdi Safaei, Sajedah Norozpour

Employee performance within the organization reflects their knowledge, skills, and values. To this end, identifying the factors, affecting the performance of employees is one of the goals of human-resource improvement in management. The effective role of motivating and reinforcing the sense of worth in an organization's personnel, in improving their efficiency, effectiveness, and productivity as well as enhancing their mental health, are factors that cannot be ignored easily. This is particularly evident in organizations where the workforce is more involved in research activities. One of the key factors is a research organization's sense of responsibility for the organizational problems of its valuable personnel. This research examines the performance diagnosing of the organizational process in Turkish universities and then identifies challenges, threats and opportunities. Finally, suggestions have been made to achieve sustainable organizational development. After identifying and examining the influencing factors, the Weisbord model is examined to evaluate the Performance Diagnosis process of issuing a work permit for foreign professors at a Turkish university. As a result of this study, researchers have made suggestions for university administrators to improve organization and staff performance.


Author(s):  
Li Jiang ◽  
Dragan Djurdjanovic ◽  
Jun Ni

The performance of machines and equipment degrades as a result of aging and wear. This decreases performance reliability and increases the potential for faults and failures. To ensure proper functionality of complex systems, advanced technologies for performance diagnosis and control are being incorporated into engineering designs, which requires an ever-increasing number of sensors and measurement devices. Nevertheless, a sensor, just as any other dynamic system, degrades and fails. A faulty sensor may cause process performance degradation, process shut down, or even a fatal accident because it is no longer able to deliver accurate information about the monitored system. Therefore, it is essential to assess sensor performance to ensure system reliability. In this paper, a method is proposed to detect, isolate, and compensate sensor degradation. The numerical algorithm for subspace state space system identification is used to track the changes of the time constants and gains of the sensor and the monitored system. Without imposing requirements for redundant sensors and measurement devices, this method utilizes the fact that sensor readings depict dynamic characteristics of the sensors as well as those of the monitored system. The newly proposed method is verified in angular sensor degradation detection using high-fidelity simulations of an automotive electronic throttle system.


1999 ◽  
Author(s):  
Luis Correas ◽  
Ángel Martínez ◽  
Antonio Valero

Abstract Diagnosis of the performance of energy was theoretically developed based on the Structural Theory (Valero, Serra and Lozano, 1993), and traditionally Thermoeconomics have usually been applied to the design of power plants and comparison between alternatives. However, the application of thermoeconomic techniques to actual power plants has always to face the generally poor quality of measurement readings from the standard field instrumentation as an unavoidable first step. The proposed methodology focuses on measurement uncertainty estimation and performance calculation by means of data reconciliation techniques, in order to obtain the most confident plant balance upon the available instrumentation. The formulation of the Structural Theory has been applied to a combined cycle, where the Fuel-Product relationships at the component level must be optimally defined for a correct malfunction interpretation. This set of relationships determines the ability to diagnose and the level of the diagnostics obtained. The paper reports the application of the methodology to a 280 MW rated combined cycle, where performance diagnosis is illustrated with results from a collection of actual operation data sets. The results show that data reconciliation yields sufficient accuracy to conduct a thermoeconomic analysis, and how the estimated impact on fuel correlates with physical causes. Hence the feasibility of thermoeconomic analysis of plant operation is demonstrated.


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