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Crystal Violet Binding Assay for Assessment of Biofilm Formation by Klebsiella pneumoniae on Catheter, Glass and Stainless-steel Surfaces
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In this paper, quantified study of the biofilm formed by Klebsiella pneumoniae isolated from urine specimen of patient suffering from acute urinary tract infection (UTI) on catheter, stainless-steel and glass coupon surfaces, as well as determine the relationship between time contact and biofilm progression using crystal-violet binding assay based on the values of optical density at 620nm of the crystal violet stain which bonded total biofilm biomass by resolubizing with 99.9% ethanol at the specific interval times. The result showed biofilm formed on three tested surfaces but in different degrees. According to obtained data, the catheter coupons presents a higher capability to attract bacteria cell and biofilm formation followed by glass surfaces while stainless-steel surfaces regard as a less attractive surfaces in bacterial adhesion and biofilm progression. The attachment of the bacterial cells on the fresh produce surfaces increase with the contact time but the increase reached a maximum at time 48h. in which, the optical densities of catheter, glass and stainless-steel coupon surfaces were (0.169 nm), (0.085 nm) and (0.07 nm) respectively. The statical analysis showed significant differences between substratum type's adherence and biofilm progression.

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
An Autocorrelative Approach for EMG Time-Frequency Analysis
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Wearable Detection Systems for Epileptic Seizure: A review
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The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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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
Wed Sep 29 2021
Journal Name
Al-khwarizmi Engineering Journal
Robust Computed Torque Control for Uncertain Robotic Manipulatorss
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This paper presents a robust control method for the trajectory control of the robotic manipulator. The standard Computed Torque Control (CTC) is an important method in the robotic control systems but its not robust to system uncertainty and external disturbance. The proposed method overcome the system uncertainty and external disturbance problems. In this paper, a robustification term has been added to the standard CTC. The stability of the proposed control method is approved by the Lyapunov stability theorem.  The performance of the presented controller is tested by MATLAB-Simulink environment and is compared with different control methods to illustrate its robustness and performance.

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Iteration for a Non-Self -Strongly Pseudocontractive Map
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Let be a Banach space, be a nonempty closed convex subset of , and be self
nonexpansive map. The sequence generated by the iterative method
, where be a contractive mapping
and is a sequence in We generalize the mapping to non-sel -Strongly
Pseudocontractive .

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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Smartphone -Based Model for Human Activity Recognition
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Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif

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Publication Date
Sat Nov 01 2014
Journal Name
Patient Preference And Adherence
Antibiotic-prescribing patterns for Iraqi patients during Ramadan
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Background: During Ramadan, Muslims fast throughout daylight hours. There is a direct link between fasting and increasing incidence of infections. Antibiotic usage for treatment of infections should be based on accurate diagnosis, with the correct dose and dosing regimen for the shortest period to avoid bacterial resistance. This study aimed to evaluate the practices of physicians in prescribing suitable antibiotics for fasting patients and the compliance of the patients in using such antibiotics at regular intervals. Materials and methods: An observational study was carried out during the middle 10 days of Ramadan 2014 in two pharmacies at Baghdad. A total of 34 prescriptions (Rx) for adults who suffered from infections were examined. For

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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Demonstration of the value of diffusion weighted MR imaging for differentiation of benign from malignant breast lesions
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Background: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast.

Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors1 and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.1 As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing wit

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
The extent of including logical intelligence in the Book of chemistry for the fifth Grade of science
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The aim of the current research to determine the extent of logical intelligence in the book of chemistry for the fifth grade of science and to achieve the goal the researcher has prepared a special criterion in the areas of logical intelligence main and sub-to be included in the book after reviewing the previous literature and studies in this regard may be the final form after presentation to experts and arbitrators in the field of Educational and psychological sciences, curricula and teaching methods from (3) main areas and (21) sub-fields, then the researcher analyzed the book Bibih and applied branches and adopted the idea of ​​both explicit and implicit as a unit of registration and repet

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