In this paper we used orthogonal basis functions and expansion coefficients for inverse modeling of magnetic data. The basis functions chosen are normalized eigenvectors of second derivation of the objective function (Hessian matrix) calculate for an initial model. Limited number of basis vectors obtained in this way defines a new subspace in model parameters space. Anew objective function is defined in term of these new parameters and minimized in subspace of original space. As in geophysical inverse problems we need to inverse matrixes that are functions data and geometry of data and model parameters. The matrix inversion in new subspace of the original space will be better conditions due to less dimensionality in the inversion. Since the most significant eigenvectors corresponding the largest Eigen values in Singular Value Decomposition (SVD) of matrixes. Others eigenvectors have less influence in fitting data or lead inversion procedures to local minima. With apply subspace method inversion will be fast and stable against the noise. The efficiency of the method is tested with synthetic and real magnetic data (acquired from Moghan area, north-west of Iran). The results proved fast convergence and stability of inversion against the noise.

One of the obvious reasons for most disorders in network service provisioning is network path congestion. Congestion avoidance in today's networks is too costly and sometimes impossible. With the introduction of SDN, centralizing the equipment's control plane has become possible. This paper presents an enhanced method named ESV-DBRA to avoid congestion in multi-tenant SDN networks. At first, ESV-DBRA monitors the traffic load and delay of all network paths for each tenant individually. Then, by merging the parameters obtained from the monitoring, the Service Level Agreements (SLA), and a novel proposed cost function, it calculates the cost of the network paths per tenant. As a result, traffic for each tenant is routed through the path/paths at the lowest possible cost from the tenant's perspective. Next, the bandwidth quotas will be calculated and assigned to the tenants over their optimal routes. Afterward, whenever congestion is likely to occur in a path, ESV-DBRA automatically changes the route or bandwidth of the tenants' traffic related to this path to avoid congestion. Related algorithms are also proposed.Eventually, simulations show that the proposed method effectively increases bandwidth utilization by 10.76%.

The Qur'an contains religious values ​​for the advancement of man to happiness. The claim is that Quranic teachings are the basis of religious values; By choosing it better, the method of proving religious beliefs can be extracted. This research tries to extract the method of proving religious beliefs with a business approach and by using artistic forms with a descriptive and analytical method and with a better selection of Quranic teachings. Based on the verses, the process was defined as the introduction to the institutionalization of religious values ​​in the businessman 1- Gaining self-knowledge (knowing the talents, capacities, existential dimensions and position of man in the universe); 2- Gaining monotheistic insight (knowing the origin and your relationship with the Creator); 3- Reciprocity is (knowing the destination and drawing the path of happiness in the universe). After the realization of these three stages, the beliefs must be proven through rational and scientific reasoning and penetrate, in this case, the acceptance of good qualities in the businessman will be facilitated.

Objective: People who have higher social health can more successfully deal with the challenges and ups and downs of playing key social roles and participate more in collective activities and prevent social deviations and anomalies. In this regard, foresight and the development of a forward-looking strategy model by the media can play an important role in promoting the social health of their audience (individuals).method: This research has been done qualitatively and quantitatively. In the qualitative phase, content analysis and Q methods were used, and in the quantitative phase, factor analysis was used to analyze the Q method data.Results: The content analysis of the media in this study showed that the most media production in the field of social deviations with 576 cases and the lowest media production in the field of violence with 237 cases. The field of social quality with 485 and the field of social issues with 312 cases are in the second and third ranks. A small questionnaire was made and based on it, the desired model was designed using PLS software. Conclusion: This model showed that the function of media is effective in promoting social health of society and can have the greatest impact on improving quality of life, reducing violence, reducing social deviations and social issues.

In this research, in order to investigate the effect of the piezoelectric patch which is used as a sensor or actuator in rotating flexible structures such as a helicopter blade, the free vibrations of the rotating rectangular sheet with and without the piezoelectric patch have been presented. First-order shear deformation theory is considered for plate displacement and piezoelectric field. Considering the effect of Coriolis acceleration, centrifugal acceleration and centrifugal in-plane forces, the equations of motion are derived from Hamilton's principle and the electromechanical couple equation is obtained from Maxwell's equation. For piezoelectric, two electrical conditions, open circuit and closed circuit, which are used in sensors and actuators, respectively, have been considered. The equations are discretized with the help of the numerical method of generalized differential squares and the matrices of inertia mass, eccentricity, Coriolis and stiffness matrix are obtained. Natural frequency values for beam and rotating plate have been compared in Abaqus software. Also, the values obtained from the numerical solution in MATLAB have been verified with articles and ABAQUS, which have high accuracy. The effect of parameters such as hub radius, rotation speed, sheet thickness, aspect ratio, piezoelectric patch thickness and applied voltage on the natural frequency of the system has also been investigated.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.