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Earthquake Hazard Mitigation for Uncertain Building Systems Based on Adaptive Synergetic Control
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This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulated on the basis of earthquake acceleration data recorded from the El Centro Imperial Valley Earthquake. The effectiveness of the adaptive synergetic control was verified and assessed via numerical simulation, and a comparison study was conducted between the adaptive and classical versions of synergetic control (SC). The vibration suppression index was used to evaluate both controllers. The numerical simulation showed the capability of the proposed adaptive controller to stabilize and to suppress the vibration of a building subjected to earthquake. In addition, the adaptive controller successfully kept the estimated viscosity and stiffness coefficients bounded.

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Publication Date
Sat Nov 05 2022
Journal Name
Sensors
Enhancement of the CAST Block Algorithm Based on Novel S-Box for Image Encryption
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Background and Aim: due to the rapid growth of data communication and multimedia system applications, security becomes a critical issue in the communication and storage of images. This study aims to improve encryption and decryption for various types of images by decreasing time consumption and strengthening security. Methodology: An algorithm is proposed for encrypting images based on the Carlisle Adams and Stafford Tavares CAST block cipher algorithm with 3D and 2D logistic maps. A chaotic function that increases the randomness in the encrypted data and images, thereby breaking the relation sequence through the encryption procedure, is introduced. The time is decreased by using three secure and private S-Boxes rather than using si

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Publication Date
Mon Jan 04 2021
Journal Name
Multimedia Tools And Applications
Attention enhancement system for college students with brain biofeedback signals based on virtual reality
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Publication Date
Thu Dec 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Cryptography based on retina information
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The security of message information has drawn more attention nowadays, so; cryptography has been used extensively. This research aims to generate secured cipher keys from retina information to increase the level of security. The proposed technique utilizes cryptography based on retina information. The main contribution is the original procedure used to generate three types of keys in one system from the retina vessel's end position and improve the technique of three systems, each with one key. The distances between the center of the diagonals of the retina image and the retina vessel's end (diagonal center-end (DCE)) represent the first key. The distances between the center of the radius of the retina and the retina vessel's end (ra

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Tue Jul 02 2013
Journal Name
Journal Of Baghdad College Of Dentistry
Local Drug Delivery Systems for Treating Periodontal Diseases: A Review of Literature
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Publication Date
Mon Apr 17 2017
Journal Name
Wireless Personal Communications
ITPMAP: An Improved Three-Pass Mutual Authentication Protocol for Secure RFID Systems
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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy logic in the estimate of reliability function for k - components systems
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Abstract:

One of the important things provided by fuzzy model is to identify the membership functions. In the fuzzy reliability applications with failure functions of the kind who cares that deals with positive variables .There are many types of membership functions studied by many researchers, including triangular membership function, trapezoidal membership function and bell-shaped membership function. In I research we used beta function. Based on this paper study classical method to obtain estimation fuzzy reliability function for both series and parallel systems.

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Publication Date
Fri Feb 05 2010
Journal Name
Etri Journal
MC-MIPOG: A Parallel t-Way Test Generation Strategy for Multicore Systems
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Publication Date
Wed Sep 17 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Local drug delivery systems for treating periodontal diseases (A review of literature)
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In this review of literature, the light will be concentrated on the local drugs delivery systems for treating the periodontal diseases. Principles, types, advantages and indications of each type will be discussed in this paper.

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Publication Date
Thu Sep 22 2016
Journal Name
Applied Sciences
Analysis and Evaluation of Performance Gains and Tradeoffs for Massive MIMO Systems
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