In earthquake engineering problems, uncertainty exists not only in the seismic excitations but also in the structure's parameters. This study investigates the influence of structural geometry, elastic modulus, mass density, and section dimension uncertainty on the stochastic earthquake response of a multi-story moment resisting frame subjected to random ground motion. The North-south component of the Ali Gharbi earthquake in 2012, Iraq, is selected as ground excitation. Using the power spectral density function (PSD), the two-dimensional finite element model of the moment resisting frame's base motion is modified to account for random ground motion. The probabilistic study of the moment resisting frame structure using stochastic fin

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     This research deals with Building A probabilistic Linear programming model  representing, the operation of production in the Middle Refinery Company (Dura, Semawa, Najaif) Considering the demand of each product (Gasoline, Kerosene,Gas Oil, Fuel Oil ).are random variables ,follows certain probability distribution, which are testing by using Statistical programme (Easy fit), thes distribution are found to be Cauchy distribution ,Erlang distribution ,Pareto distribution ,Normal distribution ,and General Extreme value distribution .              &

Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

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Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi

Car drivers hear many kinds of noise inside their vehicles' cabins, and the most annoying ones are the noise generated by tires, engines, and outside winds. Noise affects the comfort of the passengers inside the cabin, and it’s sad to say that modern cars are noisier in many kinds of noise signals due to using a lot of plastic materials in new budget cars. For expensive and luxury cars, the problem is solved by using better sound insulation materials, but for the budget ones, the approach used here is effective. It is called Active Noise Cancellation and can be done using analog or digital electronics. An operational amplifier and filters are used for the analog one, and in the digital one, signal processor chips are used. In engineeri

In this work the analysis of laser beam profile system ,using a two dimensional CCD (Charge Coupled Device) arrays, is established. The system is capable of producing video graphics that give a two dimensional image of laser beam. The video graphics system creates color distribution that represent the intensity distribution of the laser beam or the energy profile of the beam. The software used is capable of analyzing and displaying the profile in four different methods that is , color code intensity contouring , intensity shareholding, intensity cross section along two dimension x-y, and three dimensional plot of the beam intensity given in the same display.

In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

Project management are still depending on manual exchange of information based on paper documents. Where design drawings drafting by computer-aided design (CAD), but the data needed by project management software can not be extracted directly from CAD, and must be manually entered by the user. The process of calculation and collection of information from drawings and enter in the project management software needs effort and time with the possibility of errors in the transfer and enter of information. This research presents an integrated computer system for building projects where the extraction and import quantities, through the interpretation of AutoCAD drawing with MS Access database of unit costs and productivities for the pricing and

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa