Individual Performance Index Research Articles

Analysis of Remuneration System Satisfaction and Its Affecting Factors (Case Study on Specialist-Physician at Government Hospital in Jakarta)

Background:Remuneration is an important strategy to improve the competence of hospital services. Remuneration aims to motivate employees which can be achieved if the remuneration system is implemented fairly, but the gap between the ratio of the number of doctors and the average points to rates causes’ physician dissatisfaction toward the remuneration system. Objective:Analyze satisfaction level and measure remuneration satisfaction factors on Pediatricians and Obstetrics and Gynecologists at ABC Hospital Jakarta. Method:This study used quantitative methods with multiple linear regression analysis measured by the Equity Scale and Remuneration Satisfaction Scale. Interviews were used to obtain comprehensive analysis results from respondents who were in the lower and upper limits of the questionnaire results. The interview also involved the management of ABC Hospital Jakarta.Result and discussion:Total 44 respondents consisting of 30 Pediatricians and 14 Obstetricians and Gynecologists, showed dissatisfaction with the remuneration system (45,46%), neutral (31,53%), and satisfied (23%). There was a relationship between perceptions of external fairness (P= 0,003) and procedural fairness (P= 0,002) with remuneration satisfaction. There was no relationship between perceptions of internal justice (P= 0,929) and perceptions of individual justice (P= 0,130) with remuneration satisfaction. These results were explored using interviews and the causes of doctor dissatisfaction due to the gap in the achievement of the Individual Performance Index, lots of doctor examinations that were not listed in the rates, and remuneration points did not consider the complexity of each job. Meanwhile, the dissatisfaction felt by the management was due to the lack of measurement of quality indicators in the remuneration system.Conclusion and recommendation:External and procedural justices are factors that affect the satisfaction of remuneration felt by specialist-physician. The remuneration obtained at ABC Hospital Jakarta is lower than other Government Hospitals of the same type. In addition, there are binding rules, doctors' lack of understanding of the remuneration system, and lack of socialization. The management needs to formulate a more detailed remuneration system based on applicable regulations by adjusting the hospital situation.

Research on Individual Performance Index of Air Cluster Combat Aircraft Based on Differential Game Theory

UAV cluster has the characteristics of low cost, large-scale and high autonomy, and has gradually become a new research direction in the field of military intelligence, and is widely used in combat tasks such as penetration reconnaissance, lure interference, large-scale saturation attack and regional sealing and control. Therefore, air cluster confrontation will become one of the main melodies of air combat in the process of confrontation, cluster aircraft individual performance index determines the overall cluster level, poor individual performance will make the cluster cannot effectively complete the task, excellent individual performance completes the task, but will bring the increase in the cost of cluster, so in the air cluster confrontation scenario, according to the target performance reasonable our individual performance has become important. Based on the innovative differential game theory, this paper studies the effective interception of the aircraft in the cluster high dynamic pursuit scenario, studies the relationship between the individual performance of the interceptor aircraft and the target aircraft, and effectively provides reference for the overall index design of the aircraft in the military field.

A developmental outlook on the role of cognition and emotions in youth volleyball and artistic gymnastics.

Developmental and cognitive psychology recently started to take an interest in the sports domain, exploring the role of either cognitive functions or emotions in youth sport. However, to the extent that cognition and emotions are inextricably linked, studying them jointly from a developmental perspective could inform on their interplay in determining performance in different sports. This research examined the role of general cognitive abilities, attentional style, and emotions (controlling for age and experience), in predicting performance in youth volleyball and artistic gymnastics. A total of 218 female participants, of which 114 volleyball players and 104 artistic gymnasts (11–17 years old) were administered two measures of working memory and six measures of executive functions (namely inhibition, updating, and shifting). They also completed an attentional style and an emotion-related questionnaire. For each volleyball player, an individual performance index based on every gesture performed during the games and controlled for the team performance was computed. As a measure of gymnasts’ performance, scores in 2017–2018 competitions were used. Regression analysis showed that the main predictor of the volleyball players’ performance (R2 = 0.23) was a working memory-updating factor (ß = 0.45, p = 0.001), together with experience (ß = 0.29, p = 0.030) and high-arousal unpleasant emotions (ß = 0.30, p = 0.029), which positively predicted performance. Experience (ß = 0.30, p = 0.011), age (ß = −0.036, p = 0.005) and high-arousal unpleasant emotions (ß = −0.27, p = 0.030) were the predictors of gymnasts’ performance (R2 = 0.25). These results represent a first step in understanding if and how youth female athletes of open- and closed-skills sports rely on different psychological abilities. This line of research could offer insight to practitioners regarding which psychological abilities could be more relevant to train depending on the type of sport.

Individual differences in behavioral flexibility predict future volitional ethanol consumption in mice.

Cognitive control is key to regulating alcohol intake and preventing relapse. Behavioral inflexibility can prevent adaptive strategies such as mindfulness or other relapse-prevention behaviors. In a mouse model we investigated whether individual variability in behavioral flexibility (using attentional set-shifting task; ASST) predicts future alcohol intake. Adult male and female C57BL/6J mice were subjected to ASST using a bowl-digging paradigm where mice identify a baited bowl based on compound odor and textural cues. This was completed prior to any alcohol exposure. Individual performance across mice varied within the group. We integrated several metrics, specifically ASST stage completed, trials to completion, and errors performed to produce an individual performance index measure of behavioral flexibility. Afterward, ASST mice were trained to drink ethanol (15%, v/v, 1h/day) for 3-4 weeks until intake stabilized. Using this prospective approach, we identified an inverse relationship between behavioral flexibility and drinking-less-flexible mice had a propensity to consume more alcohol. Similar relationships have been identified previously in non-human primates and rats. Our results show that the relationship between alcohol and behavioral flexibility is a robust trait that is conserved across species and can be used in mice to study neural substrates underlying these behaviors.

An Enhanced Full-Form Model-Free Adaptive Controller for SISO Discrete-Time Nonlinear Systems.

This study focuses on the full-form model-free adaptive controller (FFMFAC) for SISO discrete-time nonlinear systems, and proposes enhanced FFMFAC. The proposed technique design incorporates long short-term memory neural networks (LSTMs) and fuzzy neural networks (FNNs). To be more precise, LSTMs are utilized to adjust vital parameters of the FFMFAC online. Additionally, due to the high nonlinear approximation capabilities of FNNs, pseudo gradient (PG) values of the controller are estimated online. EFFMFAC is characterized by utilizing the measured I/O data for the online training of all introduced neural networks and does not involve offline training and specific models of the controlled system. Finally, the rationality and superiority are verified by two simulations and a supporting ablation analysis. Five individual performance indices are given, and the experimental findings show that EFFMFAC outperforms all other methods. Especially compared with the FFMFAC, EFFMFAC reduces the by 21.69% and 11.21%, respectively, proving it to be applicable for SISO discrete-time nonlinear systems.

Finite-time fuzzy game-based attitude control for on-orbit cooperative transporting

Substructure transporting is an important phase for on-orbit assembly. This paper investigates a problem of designing a control approach for multiple transporting agents attached to one substructure, so as to complete the task of attitude tracking and stabilization of the substructure in the transportation process. A finite-time fuzzy game control method is developed to solve this problem. Using the framework of differential game, a finite-time nonlinear game is formulated based on the individual performance index functions of agents and attitude dynamics of the combination consisting of transporting agents and the substructure, which can reflect the cooperation and coordination between agents. In order to realize finite-time convergence which is more suitable for engineering requirement, a speed function is introduced to transfer finite-time game into infinite-time game. Considering the limited computational ability of agents, Takagi-Sugeno (T-S) fuzzy is incorporated to divide the nonlinear game problem into weighted average of multiple linear games which are easy to get the Nash equilibrium. Numerical simulations validate the efficiency of the proposed method for attitude control and the advantage in less calculation and better performance in dynamics and steady state than the existing methods.

Ultrasound speed in red deer antlers: a non–invasive correlate of density and a potential index of relative qualit

Deer antlers can be used as an index of individual performance both in ecological and productive contexts. Their quality is often measured only by their biometrical features, such as size, asymmetry or weight. Mechanic characteristics cannot normally be measured without destroying the antler and hence losing the commercial value of the trophies. Here, we studied ultrasonic velocities, density, and tensile strength across various sections of cast antlers of Iberian red deer (Cervus elaphus hispanicus). We found that the speed value depended on the section of the antler and the propagation direction. For antler sections, velocities were lowest for mid–beam and highest for brow tine. Results were similar for density and indirect tensile strength, probably related to differences in functionality among antler sections. Density explained most of the variability of ultrasound–speed. The time elapsed from antler shed affected density more than ultrasound speed. The indirect tensile strength showed a non–linear, decelerating relationship with ultrasound speed. We discuss the applications of ultrasound speed as a non–invasive tool to measure density and physical properties of antlers and antler sections, and their potential use as an index of quality.

Linear quadratic differential game approach for attitude takeover control of failed spacecraft

Spacecraft is mostly abandoned after its fuel exhausts or actuator fails. Using microsatellites to implement attitude takeover control for failed spacecraft is a cost efficient way to recycle on-board valuable payloads at a low cost. In order to achieve collaboration between independent microsatellites, a differential game based method is proposed to stabilize the combined spacecraft composed of multiple microsatellites and the failed spacecraft, in which each microsatellite can independently calculate its own control strategy. Firstly, based on the attitude model of combined spacecraft and the performance index function of each microsatellite, the linear quadratic differential game model is formulated. By optimizing individual performance index functions, the control strategies of multiple microsatellites can be obtained. Secondly, in order to find the Nash equilibrium strategies of microsatellites, the coupled Hamilton-Jacobi(HJ) equations are transferred to a set of coupled Riccati differential equations over finite time horizon. In order to avoid computational overhead, a set of coupled algebraic Riccati equations over infinite horizon is also derived, which can be solved easily with high precision by the Lyapunov iterations method. Finally, numerical simulations verify the effectiveness of the differential game method for the attitude takeover control of failed spacecraft.

Parameter Self-Tuning of SISO Compact-Form Model-Free Adaptive Controller Based on Long Short-Term Memory Neural Network

Model-free adaptive controller (MFAC) is a novel data-driven control methodology that relies only on input/output (I/O) measurement data instead of classic mathematical models of actual controlled plants. The single-input single-output (SISO) compact-form MFAC (SISO-CFMFAC) is a promising method for controlling SISO nonlinear time-varying systems. The parameters in SISO-CFMFAC must be carefully tuned before use, as inappropriate parameters may lead to poor control performance. However, up to now, parameter tuning has been a time-consuming and laborious task. In this paper, a new approach called SISO-CFMFAC-LSTM is proposed for parameter self-tuning of SISO-CFMFAC based on long short-term memory (LSTM) neural network. To evaluate the performance of the proposed methodology, qualitative and quantitative comparisons with other existing control algorithms are carried out. Six individual performance indices, namely, the root mean square error (RMSE), the integral absolute error (IAE), the integral time-weighted absolute error (ITAE), the integral absolute variation of the control signal (IAVU), the maximum overshoot (MO), and the imprecise control ratio (ICR), are introduced for quantitative comparison. The experimental results demonstrate that the proposed SISO-CFMFAC-LSTM achieves the best performance in all indices, indicating that it is an effective control method for SISO nonlinear time-varying systems.

Discrete-Time Multi-Player Games Based on Off-Policy Q-Learning

In this paper, an off-policy game Q-learning algorithm is proposed for solving linear discrete-time non-zero sum multi-player game problems. Unlike the existing Q-learning methods for solving the Riccati equation by on-policy learning approaches for multi-player games, an off-policy game Q-learning method is developed for achieving the Nash equilibrium of multiple players. To this end, first, a non-zero sum game problem is formulated, and the value function and the Q-function defined according to each-player individual performance index are rigorously proved to be linear quadratic forms. Then, based on the dynamic programming and Q-learning methods, an off-policy game Q-learning algorithm is developed to find the control policies for multi-player games, such that the Nash equilibrium is reached under the learned control policies. The merit of this paper lies in that the proposed algorithm does not require the system model parameters to be known a priori and fully utilizes measurable data to learn the Nash equilibrium solution. Moreover, there is no bias of Nash equilibrium solution when implementing the proposed off-policy game Q-learning algorithm even though probing noises are added to control policies for maintaining the persistent excitation condition. While bias of the Nash equilibrium solution could be produced if on-policy game Q-learning is employed. This is another contribution of this paper.

Global optimal constrained ICA and its application in extraction of movement related cortical potentials from single-trial EEG signals

Background and objectiveThe constrained ICA (cICA) is a recent approach which can extract the desired source signal by using prior information. cICA employs gradient-based algorithms to optimize non convex objective functions and therefore global optimum solution is not guaranteed. In this study, we propose the Global optimal constrained ICA (GocICA) algorithm for solving the conventional cICA problems. Due to the importance of movement related cortical potentials (MRCPs) for neurorehabilitation and developing a suitable mechanism for detection of movement intention, single-trial MRCP extraction is presented as an application of GocICA. MethodsIn order to evaluate the performance of the proposed technique, two kinds of datasets including simulated and real EEG data have been utilized in this paper. The GocICA method has been implemented based on the most popular meta-heuristic optimization algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Charged System Search (CSS) where the results have been compared with those of conventional cICA and two ICA-based methods (JADE and Infomax). ResultsIt was found that GocICA enhanced the extracted MRCP from multi-channel EEG better than both conventional cICA and ICA-based methods and also outperformed them in single-trial MRCP detection with higher true positive rates (TPRs) and lower false positive rates (FPRs). Moreover, CSS-cICA resulted in the greatest TPR (91.2232 ± 3.4708) and the lowest FPR (8.7465 ± 3.7705) for single-trial MRCP detection from real EEG data and the greatest signal-to-noise ratio (SNR) (39.2818) and the lowest mean square error (MSE) and individual performance index (IPI) (41.8230 and 0.0012, respectively) for single-trial MRCP extraction from simulated EEG data. ConclusionsThese results confirm the superiority of GocICA with respect to conventional cICA that is due to the ability of meta-heuristic optimization algorithms to escape from local optimal point. As such, GocICA is a promising new algorithm for single-trial MRCP detection which can be used for detecting other types of event related cortical potentials (ERPs) such as P300 and also for EEG artifact removal.

Development of paving performance index system for selection of modified asphalt binder

The objective is to establish a comprehensive paving performance index (PPI) for quantifying the cost-effectiveness of modified asphalt binders. Eight modified binders were characterized using a suite of mechanical tests for the rutting, fatigue, yield, and recovery properties. The current specification parameter for each test was evaluated to establish the individual performance index (IPI). The developed PPI considered contributions from all IPIs and was found to correlate reasonably well with cost via a linear function, except for the crumb rubber (CR) modified binder. By evaluating the binder performance per unit price, CR was identified as the most cost-effective modifier.

Regulation of relationships between heterogeneous farmers and an aquifer accounting for lag effects

Many environmental problems are due to damage caused by pollutants that accumulate with a time lag following their emission. In this study, we focus on nitrates used in agriculture, which can pollute groundwater many years after their initial application. A dynamic optimal control problem with heterogeneous farmers is proposed. The usual structural parameters such as the discount rate, the natural clearing rate and the lagged time interval between the occurrence of soil‐level pollution and the impact on groundwater are taken into account. We also examine pollution as caused by a continuous set of farms characterised by their individual performance index and by their individual marginal contribution to the pollution. The issue is further investigated by taking account of change in the information context, successively related to perfect information and to asymmetric information. As a result, when the delay between the spreading of N‐fertilizer and the impact on the aquifer increases, that is, the longer the lag, the steady‐state pollution stock and the steady‐state shadow price of the stock both increase. Moreover, we show that the optimal regulation may require a decreasing amount of fertilizer over time, even in the case of initial underpollution.

Racing performance in red blood cell hypervolemic Standardbred trotters

The association between red blood cell hypervolaemia (RCHV) and racing performance was examined in 116 Standardbred trotters referred to the clinic during a 5 year period with histories of impaired racing performance. Red cell hypervolaemia was the only significant abnormality detected in a thorough clinical examination, cell volumes ranging 116-178% of the predicted normal values. They were also compared with the performance traits of the contemporary Swedish Standardbred trotter population (n = 58,058). The performance traits were based on earnings per year and start, best annual racing time, % placings 1 to 3, and calculated individual performance indices (PI) published in the Annual Statistics for Swedish Trotting. These parameters were transformed to approach normal distributions. The results indicated that horses developing RCHV tended to have been superior athletes initially compared to the contemporary population average. After 3 to 4 years of racing (at mean age +/- s.d. 5.5 +/- 1.5 years) their racing performance declined rapidly during the year of diagnosis of RCHV. Therefore, both earning and placing traits were reduced and best racing time increased. Further, the PI, well above the population average prior to diagnosis, was reduced significantly. During the 3 year period following diagnosis, a slight improvement in racing performance was noted although it was not restored to previous racing form. It was concluded that RCHV in the Standardbred trotter may denote the end of a successful racing career.

Muscle characteristics and plasma lactate and ammonia response after racing in Standardbred trotters: relation to performance.

Blood samples from the jugular vein and muscle biopsies (gluteus medius) in 25 Standardbred trotters were obtained 5-10 min after racing. The biopsies were analysed for fibre type composition and enzymatic profile and blood samples for plasma lactate and ammonia concentrations. Muscle characteristics, plasma lactate and ammonia concentrations after racing were compared with each horse's individual performance index (IPI). The IPI is calculated annually from the individual horse's racing performance (% placing 1, 2 or 3, total annual earnings, average earning per start, and best racing record), respectively, converted to and expressed as a percentage deviation from the average record of the same sex and age group. The IPI values were 100-116. Plasma lactate concentrations were 15.0-42.7 mmol/l (mean 31.3 mmol/l) and ammonia concentrations 65-210 micromol/l (mean 141 micromol/l) after racing. Fibre type composition varied among horses (range 9-27% for Type I, 32-54% for Type IIA, and 27-46% for Type IIB). Fibre type composition, enzyme activities, plasma lactate and ammonia responses to racing were not correlated to IPI. Ten of the horses also performed a submaximal test on the track, consisting of 5 incremental 1000 m heats at approximate speeds of 9.1, 9.5, 10.0, 10.5, and 11.1 m/s. Immediately after each heat a blood sample was drawn from the jugular vein for plasma lactate analysis. Plasma lactate response to exercise differed between horses, but no correlation was seen with IPI. Muscle characteristics, plasma lactate and ammonia concentrations after racing and lactate response to a submaximal track test did not correlate with current race performance expressed as IPI in a group of horses with average or better performance capacity at the time of testing. Analysis of lactate and ammonia in blood after racing is not a valuable tool to predict an individual performance index.

Some incentives and contraints of scientific performance in economics

Spangenberg, et al. have tested hypotheses concerning' facilitators and inhibitors of scientific performance in Dutch economics. In order to examine the external validity of the findings, a comparison is made with large scale empirical studies conducted in two other countries. In order to examine the convergent validity of the overall performance measure, the relationship with other scientometric indicators is inspected. In order to test the robustness of their univariate and multivariate tests, multiple regressions were performed on three criteria: scientific productivity, citation impact, and individual performance index.

Environmental marginal cost evaluation by non-inferiority surface (power systems)

A decision-making methodology is discussed for determining the optimal generation dispatch and environmental marginal cost for power system operation with multiple conflicting objectives. In this study, the generation dispatch problems are formulated as a multiple objective optimization problem with two noncommensurable objectives (economy and environmental impacts). Each objective is optimized by Powell's method in the light of the individual performance index. Goal programming, a powerful tool for multiple criteria decision-making, is quantitatively performed to identify trade-off relations among these conflicting objectives. After a trade-off relation has been determined, sensitivity analysis is applied to evaluate the environmental marginal cost which indicates the increased portion of the monetary cost of system operation while the impact on the environment is improved. Numerical examples on a sample power system consisting of 10 buses, 11 transmission lines and five generators are provided to demonstrate the capabilities of the proposed approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>