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Offline Voice-Controlled Lower Limb Rehabilitation Robot Using Forward Kinematics and Fuzzy Command Matching
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Lower limb Rehabilitation Robots (LLRRs) assist in therapeutic tasks that involve gait recovery and joint mobility recovery of the lower limbs, in patients recovering from neurologic injuries such as stroke as well as spinal cord injury. LLRRs can sometimes be driven by preprogrammed trajectories or Inverse Kinematics (IK) trajectories, which bring increased computational demand and command supported interaction. This paper proposes an interactive control framework for LLRRs using a hybrid mix of Forward Kinematics (FK) driven movement and an offline Voice Conversational Agent (VCA), based on the Vosk speech recognition engine. The framework proposed is modular in nature that is completely “local”, running offline with no need for the Internet, preserving privacy, and not needing to send uploads cards to cloud processing units. Spoken commands, such as “forward”, “backward”, “rest”, “exercise”, and “stop” are mapped to hip and knee joint angles, which are then driven to FK equations for deriving leg segment positions in an ongoing manner. A hybrid MATLAB-Python implementation is used, where MATLAB is used for simulation and animation, while Python captures the audio input and runs the offline speech recognition component. Recognized transcripts are resolved through fuzzy command matching and are followed by a confidence gated execution to improve tolerance to Automatic Speech Recognition (ASR) variability. Under controlled conditions, command recognition accuracy ranging from 80% to 95%, with end-to-end latencies ranging from 0.89 to 1.32 sec. were seen for the evaluated commands. The performance of feasible offline voice guided interaction and reasonably smooth, anatomically consistent motion transitions, as shown in simulation, provide evidence for the working of the proposed architecture. The main contribution of the work lies in the explicit exposure of ASR offline, fuzzy command matching, applying confidence gated execution, and the use of FK based motion generation, all within a lightweight LLRR oriented framework. This should be enough substrate for future hardware validation, and phase synchronized wearables deployment.

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Isolated Word Speech Recognition Using Mixed Transform
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Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the

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Publication Date
Wed May 31 2017
Journal Name
Journal Of Engineering
Stabilization of Clay Soil Using Tyre Ash
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The planning, designing, construction of excavations and foundations in soft to very soft clay soils are always difficult. They are problematic soil that caused trouble for the structures built on them because of the low shear strength, high water content, and high compressibility. This work investigates the geotechnical behavior of soft clay by using tyre ash material burnt in air. The investigation contains the following tests: physical tests, chemical tests, consolidation test, Compaction tests, shear test, California Bearing Ratio test CBR, and model tests. These tests were done on soil samples prepared from soft clay soil; tyre ash was used in four percentages (2, 4, 6, and 8%). The results of the tests were; The soil samples which

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Public key system by using isomorphism group
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In this paper we deal with the problem of ciphering and useful from group isomorphism for construct public key cipher system, Where construction 1-EL- Gamal Algorithm. 2- key- exchange Algorithm

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Using Bernoulli Equation to Solve Burger's Equation
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In this paper we find the exact solution of Burger's equation after reducing it to Bernoulli equation. We compare this solution with that given by Kaya where he used Adomian decomposition method, the solution given by chakrone where he used the Variation iteration method (VIM)and the solution given by Eq(5)in the paper of M. Javidi. We notice that our solution is better than their solutions.

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Publication Date
Sun Feb 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
SPRITE REGION ALLOCATION USING MOTION COMPENSATION TECHNIQUE
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In this paper, the developed sprite allocation method is designed to be coherent with the introduced block-matching method in order to minimize the allocation process time for digital video. The accomplished allocation process of sprite region consists of three main steps. The first step is the detection of sprite area; where the sequence of frames belong to Group of Video sequence are analysed to detect the sprite regions which survive for long time, and to determine the sprite type (i.e., whether it is static or dynamic). Then as a second step, the flagged survived areas are passed through the gaps/islands removal stage to enhance the detected sprite areas using post-processing operations. The third step is partitioning the sprite area in

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Publication Date
Wed Jan 01 2020
Journal Name
Solid State Technology
Image Fusion Using A Convolutional Neural Network
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Image Fusion Using A Convolutional Neural Network

Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Face Identification Using Back-Propagation Adaptive Multiwavenet
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

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Publication Date
Mon Jun 22 2020
Journal Name
Baghdad Science Journal
Using Evolving Algorithms to Cryptanalysis Nonlinear Cryptosystems
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            In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) which are used for attacking one of the nonlinear cryptosystems called "shrinking generator" using different lengths of cipher text and different lengths of combined LFSRs. GA and ACO proved their good performance in finding the initial values of the combined LFSRs. This work can be considered as a warning for a stream cipher designer to avoid the weak points, which may be f

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Scopus (10)
Crossref (1)
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
FACE IDENTIFICATION USING BACK-PROPAGATION ADAPTIVE MULTIWAVENET
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

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