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BCI-Based Smart Room Control using EEG Signals
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In this paper, we implement and examine a Simulink model with electroencephalography (EEG) to control many actuators based on brain waves. This will be in great demand since it will be useful for certain individuals who are unable to access some control units that need direct contact with humans. In the beginning, ten volunteers of a wide range of (20-66) participated in this study, and the statistical measurements were first calculated for all eight channels. Then the number of channels was reduced by half according to the activation of brain regions within the utilized protocol and the processing time also decreased. Consequently, four of the participants (three males and one female) were chosen to examine the Simulink model during different actions. The model contained: input signals, data selection according to the activation regions in the brain, features extraction, classification according to the frequency ranges of each action, and an interface with an embedded system to control the actuators.

 

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Publication Date
Fri Nov 11 2011
Journal Name
Thesis
Performance Analysis of a New Compact Magneto-Rheological Proportional Control Valve for Hydraulic Actuation Using FEM and Experimental Approach
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One of the main parts in hydraulic system is directional control valve, which is needed in order to operate hydraulic actuator. Practically, a conventional directional control valve has complex construction and moving parts, such as spool. Alternatively, a proposed Magneto-rheological (MR) directional control valve can offer a better solution without any moving parts by means of MR fluid. MR fluid consists of stable suspension of micro-sized magnetic particles dispersed in carrier medium like hydrocarbon oil. The main objectives of this present research are to design a MR directional control valve using MR fluid, to analyse its magnetic circuit using FEMM software, and to study and simulate the performance of this valve. In this research, a

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Publication Date
Mon May 23 2022
Journal Name
The International Journal Of Artificial Organs
Quantitative analysis and control of the torque profile of the upper limb using a kinetic model and motion measurements
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This paper investigates a new approach to the rapid control of an upper limb exoskeleton actuator. We used a mathematical model and motion measurements of a human arm to estimate joint torque as a means to control the exoskeleton’s actuator. The proposed arm model is based on a two-pendulum configuration and is used to obtain instantaneous joint torques which are then passed into control law to regulate the actuator torque. Nine subjects volunteered to take part in the experimental protocol, in which inertial measurement units (IMUs) and a digital goniometer were used to measure and estimate the torque profiles. To validate the control law, a Simscape model was developed to simulate the arm model and control law in which measurem

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Publication Date
Tue Nov 09 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of the use of automated accounting systems technology in enhancing the efficiency and effectiveness of the internal control system.: دراسة تحليلية لعينة من الموظفين العاملين في اقسام المحاسبة والتدقيق في الجامعات البحرينية
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The research aims to show the relationship between the use of automated accounting systems technology and its impact on enhancing the efficiency and effectiveness of the internal control system in a sample of Bahraini universities in light of the rapid changes in the                                       electronic business environment. Automated accounting and its impact on enhancing the efficiency and effectiveness of the internal control system, and it is concluded through the analytical study of the research sample that there is a percenta

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Determine the best model to predict the consumption of electric energy in the southern region
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Abstract:          

                Interest in the topic of prediction has increased in recent years and appeared modern methods such as Artificial Neural Networks models, if these methods are able to learn and adapt self with any model, and does not require assumptions on the nature of the time series. On the other hand, the methods currently used to predict the classic method such as Box-Jenkins may be difficult to diagnose chain and modeling because they assume strict conditions.

  

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Publication Date
Fri Jan 01 2021
Journal Name
E3s Web Of Conferences
Dewatering System Control by MATLAB Software
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The aim was to design a MATLAB program to calculate the phreatic surface of the multi-well system and present the graphical shape of the water table drawdown induced by water extraction. Dupuit’s assumption is the base for representing the dewatering curve. The program will offer the volume of water to be extracted, the total number of wells, and the spacing between them as well as the expected settlement of soil surrounding the dewatering foundation pit. The dewatering well arrangement is required in execution works, and it needs more attention due to the settlement produced from increasing effective stress.

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Publication Date
Sat Dec 31 2011
Journal Name
Al-khwarizmi Engineering Journal
Path Planning Control for Mobile Robot
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Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process.

This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and

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Publication Date
Sun Apr 02 2023
Journal Name
Narst 2023 Annual International Conference
Measuring Claim-Evidence-Reasoning Using Scenario-based Assessments Grounded in Real-world Issues
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Improving students’ use of argumentation is front and center in the increasing emphasis on scientific practice in K-12 Science and STEM programs. We explore the construct validity of scenario-based assessments of claim-evidence-reasoning (CER) and the structure of the CER construct with respect to a learning progression framework. We also seek to understand how middle school students progress. Establishing the purpose of an argument is a competency that a majority of middle school students meet, whereas quantitative reasoning is the most difficult, and the Rasch model indicates that the competencies form a unidimensional hierarchy of skills. We also find no evidence of differential item functioning between different scenarios, suggesting

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Publication Date
Sun Nov 01 2009
Journal Name
Tencon 2009 - 2009 Ieee Region 10 Conference
The effect of using XCAST based routing protocol in wireless ad hoc networks
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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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