This study adopts an integrated performance measurement and prediction model based on a combination of earned value management approach and the Learning Curve theory under risk condition. The present research to be presented has two main parts: One that concerns the project performance measurement and a second that focuses on forecasting performance indicators in terms of time and cost of the project subject to the errors and risks. The contributions of the present study are threefold. First، this study extends to the traditional performance measurement models، which focuses only on forecasting time at completion، by extending the performance measurement domain to analyse both time and cost. Second، the Learning Curve models are explicitly used as a basis to assess the nonlinear effect of Learning on the performance. Novel risk performance metrics are proposed and adopted for knowledge-based projects. Third، compared with classic deterministic and static performance measurement models، the proposed performance assessment analysis utilizes the Kalman-filter to predict the final time and cost performance accurately by taking into account the probabilistic risk factors and the errors in the performance forecasting procedures. The validity of the integrated performance measurement model is justified based on a case study. The computational results demonstrate that the developed performance measurement framework affords more accurate forecasts for the future performance compared with the traditional deterministic earned value methodology. The integrated performance measurement model developed in this study affords probabilistic prediction bounds and generated low errors than those achieved in classic EVM.

One of the factors that can be the link between our intentions and actions and their external consequences is human agency, which indicates the conscious design and intentional execution of actions by the individual in order to influence future events.Objective and Method: This research with a developmental approach of psychometric method and method 1, examines the psychometric indices of the Human Factor Characteristics Scale using the classical theory of test score measurement and the graduated question-answer theory. The purpose of this study, which included high school students in Tehran, was selected by cluster sampling of 500 people as a sample size and statistical analysis was performed on 481 data. To collect the data, the ion Human Agent Characteristics Scale (2011) was used and the research questions were evaluated using IRTPRO and SPSS software.Results:The assumption of local independence based on Pearson x2 index was established by applying Simjima's calibrated question-answer theory and the assumption of being one-dimensional based on the analysis of multidimensional question-answer theory. Diagnosis parameters with question-answer approach and classical approach Test score Both item 25 approach had the lowest and item 2 had the highest diagnosis parameter. The answer thresholds for all the questions were so far apart that no option was covered by the other option, and the options were independently selected by individuals at intervals of theta. The total scale was calculated with Cronbach's alpha of 0.945, intentionality of 0.894, foresight of 0.780, self-reactivity of 0.871 and rethinking of 0.762. Also, the role of each item in internal consistency was investigated by the loop method, which all questions had a favorable role in internal consistency of this scale. The value of the validity coefficient obtained from the question-answer theory was obtained by marginal method for intentionality 0.92, forethought 0.85, self-reaction 0.91, rethinking 0.83..

Background: Retroperitoneoscopic donor nephrectomy (RDN) is a well-established modality for the procurement of kidneys for renal transplantation. However the Learning Curve of pure RDN is not yet defined. Defining the Learning Curve will help in proper mentorship of the new donor surgeons besides providing safety to the donors.Objective: To define the Learning Curve of pure RDN.Methods: We analyzed the prospectively collected data of 102 voluntary kidney donors who underwent RDN by a single surgeon between August 2012 and April 2015 at our center. The donors were classified into group A (1–34), group B (35–68), and group C (69–102) according to the chronological order of their surgery. Left RDN was performed in 28 (82%), 25 (74%), and 28 (82%) donors of group A, B, and C, respectively. Right RDN was performed in 6 (18%), 9 (26%), and 6 (18%) donors of group A, B, and C, respectively. The clinical data were analyzed for each group.Results: Statistically significant difference was observed for the mean operative time (p<0.01) and warm ischemia time (p<0.04). The operative time remained around 200 minutes after the initial 35 cases.Conclusion: The Learning Curve of pure RDN was 35 cases, although the mastery requires more number of cases to be performed.

Modeling vadose zone, particularly the soil water characteristic Curve, plays an essential role in unsaturated soil mechanics. This Curve depends on such factors as particle size and distribution. A computational procedure acceptable for the assessment of the soil-water characteristic Curve is modeling pore size distribution from particle size distribution. In this paper, a model is proposed that considers the variation in local void ratio and evaluates its effect on the soil-water characteristic Curve in granular soils with different particle size distributions. Comparison of the results with experimental data shows that the model will predict the soil-water characteristic Curve more accurately if a direct relation is established between local void ratio and particle size.