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Recognition of Upper Limb Movements Based on Hybrid EEG and EMG Signals for Human-Robot Interaction
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Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that using mean absolute value (MAV), waveform length (WL), Wilson Amplitude (WAMP), Sine Slope Changes (SSC), and Cardinality features of the proposed algorithm achieves a classification accuracy of 89.6% when classifying seven distinct types of hand and wrist movement. Index Terms— Human Robot Interaction, Bio-signals Analysis, LDA classifier.

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Publication Date
Wed Aug 01 2012
Journal Name
I-manger's Journal On Information Technology
A MODULE FOR ENHANCING RECOGNITION SYSTEM FOR QR CODE SCANNED IMAGE
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A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

Publication Date
Fri Jul 01 2022
Journal Name
Ieee Transactions On Systems, Man, And Cybernetics: Systems
Design of Robust Terminal Sliding Mode Control for Underactuated Flexible Joint Robot
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Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

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Publication Date
Sun Oct 01 2023
Journal Name
Optical Fiber Technology
A taper-in-etch based hybrid fiber Mach-Zehnder interferometer hydrogen sensor
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Simulation and Experimental Walking Pattern Generation for Two Types of Degrees of Freedom Bipedal Locomotion Robot
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Humanoids or bipedal robots are other kinds of robots that have legs. The balance of humanoids is the general problem in these types when the other in the support phase and the leg in the swing phase. In this work, the walking pattern generation is studied by MATLAB for two types of degrees of freedom, 10 and 17 degrees of freedom. Besides, the KHR-2HV simulation model is used to simulate the experimental results by Webots. Similarly, Arduino and LOBOT LSC microcontrollers are used to program the bipedal robot. After the several methods for programming the bipedal robot by Arduino microcontroller, LOBOT LSC-32 driver model is the better than PCA 96685 Driver-16 channel servo driver for programming the bipedal walking rob

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Publication Date
Wed Jan 07 2026
Journal Name
Sport Culture
Some bio-motor abilities and their relationship to the skill of standing on the hands followed by the forward roll on the mat of floor movements in artistic gymnastics for women
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The research consists of five chapters, and in the first chapter, it addresses the introduction and importance of the research, where the researcher explained the importance of bio-motor abilities and their role in achieving a high level through their connection to the skill performance of standing on the hands followed by the forward roll, and the research problem: Do these bio-motor abilities have an impact on the level of skill performance? Handstand followed by forward roll.

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Publication Date
Tue Jun 30 2009
Journal Name
Al-kindy College Medical Journal
Incidence of Injuries to Major Blood Vessels in the Lower Limb
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Background: Blood vessels injury is one of the most
common causes of medical emergencies that admitted to
hospitals and at the same time it regarded as one of the
most important causes of death. They may represent less
than 15% of all injuries; they deserve special attention
because of their severe complications.
Objective: The aim of the present study is to assess
anatomically the injures of major arteries and veins in the
lower limb with their management.
Methods: The present study extended from April 2006 to
February 2007, in which 65 patients with lower limb
vascular injury were examined in Emergency Department
and Forensic Medicine Department of Tikrit Teaching
Hospital in Salah-Aldin governora

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Sat Jun 01 2024
Journal Name
International Journal Of Advanced And Applied Sciences
High-accuracy models for iris recognition with merging features
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Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info

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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
On the Split Mersenne and Mersenne-Lucas Hybrid Quaternions
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In this communication, introduce the split Mersenne and Mersenne-Lucas hybrid quaternions, also obtaining generating functions and Binet formulas for these hybrid quaternions and investigating some properties among them.

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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