In the present investigation, our main aim is to introduce a certain subclass of analytic univalent functions related to the Error function. We discuss the implications of our main results, including the coefficient bound, extreme points, weighted mean, convolution, convexity, and radii properties, as well as any other related properties.

Let X1, ..., Xn be a random sample from a normal distribution with unknown mean q and known variance s2. The usual estimator of the mean, i.e., sample mean, is the maximum likelihood estimator which under squared Error loss function is minimax and admissible estimator. In many practical situations, q is known in advance to lie in an interval, say [-m, m] for some m>0. In this case, the maximum likelihood estimator changes and dominates X- but it is no longer admissible. Minimax and some other estimators for this problem have been studied by some researchers. In this paper, a new estimator is proposed and the risk function of it is compared with some other competitors. According to our findings, the use of X- and the maximum likelihood estimator is not recommended when some information are accessible about the finite bounds on [-m, m] in advance. Based on the values taken by q in [-m, m], the appropriate estimator is suggested.

Modern control systems widely use network to decrease the implementation cost and also increase the performance. Although they have several advantages, they suffer from some limitations and deficiencies. Packet loss is one of the main limitations which affect the control system in different conditions and finally can lead to system instability. To prevent such problems it is important to model the system properly. In this paper, a new function has been proposed for Error modeling. Moreover, different influences of system parameters and packet loss on Error function have been investigated and it has been determined that changes of which parameter has more contribution on packet effect in Error function. Considering these parameters is very critical in designing systems.

Introduction: Exposure to music and temperature variations can influence physiological state and impact human Error. This study aims to investigate the combined and independent effects of music and temperature changes on heart rate (HR) and human Error. Materials and Methods: This interventional study was conducted on 14 participants (7 men and 7 women) under controlled conditions in 2018. The subjects experienced four types of music (Rock, Rap, Pop, and Iranian traditional music) at the noise pressure level of 75 dB, along with temperatures of 20, 25, and 30 °C independently and in combination, within an acoustic room with controlled temperature conditions. HR and human Error rate were measured using a HR meter and a researcher-made text with spelling mistakes, respectively. Results: Using SPSS 19, data analysis revealed that exposure to traditional Iranian and rock music in temperatures deviating by 5 °C from 25 °C was associated with increased Errors in detecting spelling mistakes (p < 0.05). Interestingly, traditional and rock music did not significantly affect HR across temperatures of 20, 25, and 30 °C (p > 0.05). Conclusion: Listening to traditional Iranian and rock music in conditions with approximately 5 °C cooler or warmer than room temperature can have a positive and constructive effect on HR and reduce human Error. The use of this type of music has potential implications for optimizing environmental conditions, especially in workplaces where such factors are critical.

The knowledge about the money demand function and its effecting factors is the most important ubject in Examination of the effects of monetary policies on economiy in order that the monetary policy can help monetary authorites to achive their goals by effecting money demand.This paper estimates the demand of money in Iran over 1350-1390 period using co-integration and Error correction methodology.The analysis shows that narrow definition of money (M1), domestic gross production, real exchange rate, prices level and return rate on long-term deposit are integrated. Thus, using Johansen-Juselius cointegration approach, the long-term demand for money is specified and estimated.Empirical results show that there are two co-integrated vectors among variables. In this model the coefficient of Error correction term is equal to -0.52 which is found statistically significant. This means that 52 percent of Error in each period will be corrected in long run trend. Also we find that the income elasticity of demand for money is equal to 1.82 which shows that one percent increase in income, lead to 1.82 percent increase in money demand. The positive income elasticity of demand for money is consistent with related economic theories. Moreover the coefficients of rate of return on long-term deposit and real exchange rate equals -0.82 and -0.34 respectively, which shows that one unit increase in return rate on long-term deposit and one percent increase in real exchange rate, leads to -0.82 unit and -0.34 percent decrease in money demand that show substitution of money in Iran is confirmed. Finaly results showed that money demand function during this period was stable.