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Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory
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Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) classifier and a Deep Learning (DL) approach employing the Long Short-Term Memory (LSTM) classifier to evaluate the classification accuracy of the different motions. Experimental results demonstrate that the LSTM classifier outperforms the LDA-based approach in gesture recognition, thereby offering a more effective solution for prosthesis control.

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Publication Date
Fri Jan 05 2018
Journal Name
International Journal Of Science And Research (ijsr)
Comparative Study of Some Antibiotic Resistance, Extended Spectrum ß-Lactamases (ESBLs), Metallo ß-Lactamases (MBLs) Produced in Pseudomonas aeruginosa Isolated from Clinical and Food Samples
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A total number of 33 isolates of Pseudomoans aeruginosa were collected from different clinical samples, such as: burn, wound and urine from patients attending Al-Yarmouk teaching hospital and some private clinical laboratories in Baghdad city through the period from October to December 2016. On the other hand, 21 isolates of P. aeruginosa were collected from 38 different food samples; such as: vegetables and fruits, from different local markets in Baghdad city during the period from November to December 2016. All isolates were identified by using different bacteriological and biochemical assays and confirmed by Vitek-2 identification system. The antimicrobial susceptibility test for clinical and food isolates towards 17 antimicrobial a

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Analysis of a harvested discrete-time biological models
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This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.

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Publication Date
Wed Jun 28 2023
Journal Name
Al–bahith Al–a'alami
Is it Time to Develop Government Communication Functions?
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Embracing digital technological advancements in media and communication has led government entities to adopt communication practices fully aligned with the digital and networked system in government communication. Traditional media practices within the government environment increasingly rely on the ability to utilize digital tools and systems for content creation, communication, evaluation, and the management of the entire communication process within an electronic and intelligent framework for government services. Naturally, this transformation has caught the attention of communication and public relations researchers worldwide, as the digital and networked aspects of government communication now form an intelle

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Network Traffic Prediction Based on Time Series Modeling
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    Predicting the network traffic of web pages is one of the areas that has increased focus in recent years. Modeling traffic helps find strategies for distributing network loads, identifying user behaviors and malicious traffic, and predicting future trends. Many statistical and intelligent methods have been studied to predict web traffic using time series of network traffic. In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression, and Random Forest), and comparing the performance of the models using (SMAPE) and

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Publication Date
Sun Dec 16 2018
Journal Name
Al-academy
Deconstruction the Theatrical Time in the Expressionist Doctrine
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Time affects all elements of the intellectual scene or the theatrical scene. It came along with the theatrical doctrines according to the conditions of those doctrines and their conceptual ideas or the method of their mechanisms in the application. While it is classically or realistically integrated, we see it in the expressionist doctrine inconsistent and its inconsistency makes it responsive for the deconstruction strategy. Hence the researcher entitled his study (deconstruction the theatrical time in the expressionist doctrine) so that deconstruction would be a field for his study.   The study starts with an introduction presenting the research problem, importance and objective. The theoretical framework consisted of three s

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Influence of Aging Time on Asphalt Pavement Performance
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Aging of asphalt pavements typically occurs through oxidation of the asphalt and evaporation of the lighter maltenes from the binder. The main objective of this study is to evaluate influence of aging on performance of asphalt paving materials.nAsphalt concrete mixtures, were prepared, and subjected to short term aging (STA) procedure which involved heating the loose mixtures in an oven for two aging period of (4 and 8) hours at a temperature of 135 o C. Then it was subject to Long term aging (LTA) procedure using (2 and 5) days aging periods at 85 o C for Marshall compacted specimens. The effect of aging periods on properties of asphalt concrete at optimum asphalt content such as Marshall Properties, indirect tensile strength at 25 o C,

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Optimized Artificial Neural network models to time series
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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

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Publication Date
Wed Jul 29 2020
Journal Name
Iraqi Journal Of Science
Factors Affecting Application Launch Time with Android OS
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Android OS is developing very fast, and because of being an open source OS, it is vulnerable to many problems that are manifested to users directly or indirectly. Poor application launch time is one of these problems. In this paper, a set of sixteen experiments is established to distinguish the factors that have the most evident effects on application launch time in Android mobiles. These factors are application, launch and kill, events, and storage. Mann Kendall (MK) test, one way analysis of variance (ANOVA), and Design of Experiment (DOE) are used to prove the influence of factors statistically. As a result of the experiments, the application factor, especially the third party applications level, has the most prominent effects on appl

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Publication Date
Tue Apr 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Structural Time Series for Forecasting Oil Prices
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There are many methods of forecasting, and these methods take data only, analyze it, make a prediction by analyzing, neglect the prior information side and do not considering the fluctuations that occur overtime. The best way to forecast oil prices that takes the fluctuations that occur overtime and is updated by entering prior information is the Bayesian structural time series (BSTS) method. Oil prices fluctuations have an important role in economic so predictions of future oil prices that are crucial for many countries whose economies depend mainly on oil, such as Iraq. Oil prices directly affect the health of the economy. Thus, it is necessary to forecast future oil price with models adapted for emerging events. In this article, we st

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Public Budget and the Roles of Legislative and Executive Power Regarding It with Reference to Iraq)2004-2011)
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The public budget is regarded a main tool for economic and social development. The preparation of the public budget constitute an important stream which enriches the developmental efforts and the definition of its priorities, therefore it is the focus point of many specializations. The public budget has numerous functions. It is a means to precise and to execute the political and economic goals of the executive authority, a mirror of the economic structure which reflects its strength and weakness points, specifies its revenues and others. Since the parliament is the voice of the society which expresses its interests, then, it must monitor the performance of the government so that the participation of the legislative authority in

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