This study focuses on the modeling of manufactured damper when used in steel buildings. The main aim of the manufactured dampers is to protect the steel buildings from the damaging effects that may result due to earthquakes by introducing an extra damping in addition to the traditional damping.
Only Pure Manufactured Dampers, has been considered in this study. Viscous modeling of damping is generally preferred in structural engineering as it leads to a linear model then it has been used during this study to simulate the behavior of the Pure Manufactured Damper.
After definition of structural parameters of a manufactured damper (its stiffness and its damping) it can be used as a structural element that can be added to a mathematica

      In this work, four electronic states ( ,   , and   ) of some diatomic molecules (InF and InCl) was studied by TD-DFT with energy represented by the exchange-correlation energy. The SAOP/ATZP model was applied here to determine all parameters (r_e, B_e, D_e, , , T_e , and were determined to creation reliable values for electron spectroscopy. Also, another set of this calculation has been used represented by two theoretical models: ATZP and et-QZ3P-xD model. Therefore these theoretical models for (   and   , and   ) of the molecules have been compared with many values, theoretical and experimental values,  and appear converge

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

In this paper, two of the local search algorithms are used (genetic algorithm and particle swarm optimization), in scheduling number of products (n jobs) on a single machine to minimize a multi-objective function which is denoted as  (total completion time, total tardiness, total earliness and the total late work). A branch and bound (BAB) method is used for comparing the results for (n) jobs starting from (5-18). The results show that the two algorithms have found the optimal and near optimal solutions in an appropriate times.

   The research aims to identify the importance of using the style of the cost on the basis of activity -oriented in time TDABC and its role in determining the cost of products more equitably and thus its impact on the policy of allocation of resources through the reverse of the changes that occur on an ongoing basis in the specification of the products and thus the change in the nature and type of operations . The research was conducted at the General Company for Textile Industries Wasit / knitting socks factory was based on research into the hypothesis main of that ( possible to calculate the cost of activities that cause the production through the time it takes to run these activities can then be re- distributed product cost

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