In this paper, a novel risk-based, two-objective (technical and economical) Optimal reactive power dispatch method in a wind-integrated power system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive power generation and active power loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the wind speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive power resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.

Sluggish Cognitive Tempo is used to describe a particular type of attention deficit, concentration, and slowness in information processing. The aim of this study was to investigate the psychometric properties of the Sluggish Cognitive Tempo Scale (SCTS) of the parent form among Iranian children. The present study is a descriptive study. A sample of 1700 people was selected from the provinces of Tehran, East Azerbaijan, West Azerbaijan, Kurdistan, Fars and Khorasan using cluster sampling method. 122 subjects were excluded from statistical analysis due to incomplete answers to the questionnaires and thus the final sample was reduced to 1578 parents. The confirmatory factor analysis method and internal consistency were used to compute the Sluggish Cognitive Tempo Scale factorial validity and reliability, respectively. Also, in order to examine the construct validity of the Sluggish Cognitive Tempo Scale, we computed correlations between different dimensions of Sluggish Cognitive Tempo Scale with Attention Deficit Subscale of Mental Health Assessment Questionnaire for Children and Adolescents. The results of statistical results showed that this scale has structural validity, criterion and convergence in Iranian society. The results indicate that the scale is three factors and also the validity of the scale using Cronbach's alpha method and retest test after Approved two weeks. According to the findings of the present study, the parent form of the Sluggish Cognitive Tempo Scale (SCTS) has a good validity and reliability and it can be used in research related to slow cognitive multiplication in Iranian society.

Objective Flexible Manufacturing Systems (FMS) are integrated workstations that utilize computer-controlled equipment components for production. These systems are managed by a central computer, which significantly enhances the efficiency and productivity of the production process. Accordingly, a case study is conducted on an FMS electrical manufacturing system with complex manufacturing processes, where automation on the production line is crucial. Selecting the Optimal number of advanced equipment is a challenging and vital issue for managers aiming to boost productivity and efficiently fulfill customer orders. It is a hard-to-change model, and replacing equipment incurs substantial costs.   Methods This study employs the two-stage D-Optimal method to optimize the combination of FMS elements and equipment. The D-Optimal response level input is derived from discrete-event simulation results. Depending on the conditions, various FMS equipment is allocated to each process. Each simulation result for element combinations serves as input for the experimental design. Additionally, the response level (y) of experiments from various FMS indexes is calculated using a weighting method. To reduce the number of experiments and increase data accuracy in a case study with hard-to-change parameters, all combinations are categorized based on the number of automated and manual equipment. The two stages of the D-Optimal design are defined as follows: In the first stage, all combinations within these categories are investigated. In the second stage, the optimized combination from the first stage is analyzed to determine the best configuration. Experiments in the top category from the first stage are simulated and further evaluated in the second stage of the D-Optimal method.   Results In the first phase, all advanced production equipment and FMS elements were considered. After selecting the best-calculated “y” value, which was 147,133.09 in this category, another D-Optimal design was optimized in the second phase to determine the best combination. This combination yielded a “y” value of 151,317.88, representing an improvement over the best category in the first phase of the D-Optimal design. Consequently, the optimized combination from the first phase was further refined. The results from the developed D-Optimal method and the second phase indicate that the Optimal combination of equipment involves using automated and FMS equipment for approximately 92.8% of the total components. Finally, a list of recommended FMS equipment is provided, and its productivity is compared with the productivity at the current level and a higher degree of automation for this production line.   Conclusion In summary, the results of the experimental design show that using advanced production systems does not necessarily improve system efficiency, and determining Optimal combinations requires accurate calculations.

In order to study the spatial structure of oriental beech (Fagus orientalis Lipsky) stand at Optimal stage, this research was carried out in the Caspian forests of Iran. The studied site consisted of a natural stand located at Sangdeh district (Mers-e-se) with three hectare area. It is located between 1900 and1950 m.a.s.l. Six sample plots each with 0.36 ha area, were systematically selected and all trees (1244 stem) within the plots were measured and recorded. Using increment borer, the mean age of the stand was estimated as 137 years; the age difference of trees was 40 years. Results showed that the stand has a closed canopy cover and distribution of stem number per diameter class was more or less homogenous (Bell shape) with a semi even-aged structure. Using Ripley's K function, the distribution of trees within the stand was random.

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..

AbstractThe aim of this study was to investigate the validity, reliability and factor structure of the "How I Think" questionnaire to assess cognitive distortions in Iranian students. The present research design is descriptive and psychometric studies. The statistical population of this study included all male high school students in city Dezful in the academic year 1399-1400, from which 316 students were selected by multi-stage random sampling and completed the How I think and Bass and Perry Aggression Questionnaires (for Convergent validity). Factor analysis, Cronbach's alpha and Pearson correlation were used to analyze the data using SPSS and AMOS 20 software. The results of factor analysis showed that the questionnaire consists of six factors and has good fit indices. The convergent validity of this questionnaire indicated a satisfactory correlation between the dimensions of the scale "How I think" with the Aggression Questionnaire (p <0.01). Cronbach's alpha and Split- half coefficients for the whole scale and its dimensions ranged from 0.66 to 0.92.The conclusion is that the Persian version of the "How do I think" questionnaire for measuring cognitive distortions in Iranian students has acceptable psychometric properties and can be used as a valid tool in research, educational and clinical situations.

One of the important issues in the production of concrete is environmental variability that affects the concrete and elements constructed from this material. Due to the importance of different characteristics of concrete in short- and long-term conditions, this article aims to investigate the influence of initial temperature conditions of self-compacting concrete on its long-term characteristics and determine the initial Optimal temperature of concrete. For these purposes, several experiments under three temperature conditions of 5, 20, and 40 degree-of-Celsius were conducted to evaluate the rheology and mechanical properties of fresh concrete in the range of 7 and 28 days. In these experiments, alternative mineral admixtures of cement such as micro-silica, fly ash, and zeolite were used to build the concrete specimens. Results demonstrate that the mechanical properties of the specimens increase with increasing initial temperature in the short term, while such properties significantly decrease in the long term compared to the specimens constructed under lower initial temperature. Moreover, the fluidity of self-compacting concrete increases with increasing initial temperature.

Many real-world applications require minimization of a cost function. This function is the criterion that figures out Optimally. In the control engineering, this criterion is used in the design of Optimal controllers. Cost function optimization has difficulties including calculating gradient function and lack of information about the system and the control loop. In this article, for the first time, gradient memetic evolutionary programming is proposed for minimization of non-convex cost functions that have been defined in control engineering. Moreover, stability and convergence of the proposed algorithm are proved. Besides, it is modified to be used in online optimization. To achieve this, the sign of the gradient function is utilized. For calculating the sign of the gradient, there is no need to know the cost-function’s shape. The gradient functions are estimated by the algorithm. The proposed algorithm is used to design a PI controller for nonlinear benchmark system CSTR (Continuous Stirred Tank Reactor) by online and offline approaches.

In this paper the Optimal control of boundary heat flux in a 2-D solid body with an arbitrary shape is performed in order to achieve the desired temperature distribution at a given time interval. The boundary of the body is subdivided into a number of components. On each component a time-dependent heat flux is applied which is independent of the others. Since the thermophysical properties are temperature dependent, the problem is treated as a nonlinear inverse heat conduction problem. Conjugate gradient method (CGM) along with adjoint problem is utilized in order to solve the inverse problem. Optimization process is employed for the heat flux imposed on each of the boundary component individually which was previously shown to be more efficient than optimizing the entire heat flux array simultaneously. Three versions of CGM; that is, the Fletcher-Reeves (FR), Polak-Ribiere (PR) and Powell-Beale are utilized for comparison. As a test case, heating of an Aluminum bar with a square cross section and temperature-dependent thermo-physical properties is considered. Results show that for large time-steps the Powell-Beale version with normalized search direction, and for small time-steps the Polak-Ribiere version are the most efficient method with the least error in the estimated temperature field. Moreover, for large time step size results show that addition of regularization term to the Error Function reduces the amplitude of oscillations in the estimated heat flux.

Optimality conditions for consumption behavior with liquidity constraints are obtained using the functional recurrence equation in Bellman's dynamic programming and the generalized Hamiltonian function in Pontryagin's maximum principle. The rejection of Hall's random walk hypothesis is then established for liquidity constrained consumers. An explicit mathematical relation is formulated which demonstrates the effects of liquidity constraints on consumption, which implies that under certain conditions the liquidity constraint may shift the Optimal consumption profile forward even when the rate of time preference exceeds the interest rate. Our analysis is further developed to time-varying interest rates. Using the Kuhn-Tucker conditions, we have shown the interactions between the time-varying interest rate, the utility discount rate and the severity of liquidity constraints. It is shown, using the coefficient of absolute risk aversion, that how the time-varying interest rate may affect Optimal consumption through intertemporal elasticity of substitution. Simultaneous effects of the pure preference parameters, interest rates variations and the liquidity constraints on Optimal consumption path are mathematically formulated.Limitations in Optimal control applications in modeling Optimal consumption with liquidity constraints in a stochastic environment are briefly examined.