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Active Vibration Suppression of Smart Cantilever Beam with Sliding Mode Observer Using Two Piezoelectric Patches
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This paper presents a vibration suppression control design of cantilever beam using two piezoelectric ‎patches. One patch was used as ‎an actuator element, while the other was used as a sensor. The controller design was designed via the balance realization reduction method to elect the reduced order model that is most controllable and observable. ‎the sliding mode observer was designed to estimate six states from the reduced order model but three states are only used in the control law. Estimating a number of states larger than that used is in order to increase the estimation accuracy. Moreover, the state ‎estimation error is proved bounded. An ‎optimal LQR controller is designed then using the ‎estimated states with the sliding mode observer, to ‎suppress the vibration of a smart cantilever ‎beam via the piezoelectric elements. The control spillover problem was avoided, by deriving an avoidance ‎condition, to ensure the ‎asymptotic stability for the proposed vibration ‎control design. ‎The numerical simulations were achieved to ‎test the vibration attenuation ability of the ‎proposed optimal control. For 15 mm initial tip ‎displacement, the piezoelectric actuator found ‎able to reduce the tip displacement to about 0.1 ‎mm after 4s, while it was 1.5 mm in the ‎open loop case.  The current experimental results showed a good performance of the proposed LQR control law and the sliding mode observer, as well a good agreement with theoretical results.

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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6
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The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

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Publication Date
Mon Feb 26 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
10.28936 USING NATTOKINASE IN CHEDDAR RIPENING: USING NATTOKINASE IN CHEDDAR RIPENING
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The crude enzyme Nattokinase produced by Bacillus subtilis was used in ripening cheddar cheese by adding three concentration of enzyme 80, 160 and 320mg/Kg beside the control treatment without enzyme, the product was checked for three months to determine humidity, protein, fat, non-protein nitrogen, soluble nitrogen and pH, sensory evaluation was conducted, it was noticed that the variety in protein percentages and the soluble nitrogen percentage during second month of ripening for T2, T3 and T4 treatments were (11.2, 15.54 and 18.48) respectively, in comparison with control which was 7.6%, while in the third month it was (17.37, 20.67 and 22.26) respectively, in comparison with control which was only 10%, on the other hand, non-protein

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Penetration of charged particles in ZnO using energy loss function model
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In this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less

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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of The College Of Education For Women
Qualities of Life Partner from the Perspective of a Sample of University Students
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The study aims at identifying the morphological and psycho-socio-economic qualities wished to be in a life partner among a sample of Palestinian youth. The total sample was (231) and consisted of  (83) male and (148) female students. Each student presented a detailed report on the qualities he/she wished to be in life partner. The study used the descriptive approach and content analysis method. The validity and stability of the analysis were calculated. The results showed eight qualities in both groups: physical, psychological, emotional, social, intellectual, familial, economic and academic. Female students were found to have more variations than male students in terms of the qualities preferable in the life partner. Male students

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Determination of bacterial contamination of milk using fluorometry
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The aim of this paper is to determine the feasibility of using fluorometric methods as an indicator for quality and contamination of milk with E.coli bacteria, and selection the suitable wavelength to be used with laser induced auto fluorescence. Three groups of milk samples were used in this study: Fresh pasteurized milk samples, milk samples containing different concentration of E.coli bacteria which were added artificially, and milk samples that were kept in refrigerator for 3-5 days. Thirteen excitation wavelengths were used to get the emission spectra for all milk samples using spectroflourometer .The results showed that the emission spectra at 275nm excitation wavelength gave a good differentiation between these three groups.

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Local Dependence for Bivariate Weibull Distributions Created by Archimedean Copula
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In multivariate survival analysis, estimating the multivariate distribution functions and then measuring the association between survival times are of great interest. Copula functions, such as Archimedean Copulas, are commonly used to estimate the unknown bivariate distributions based on known marginal functions. In this paper the feasibility of using the idea of local dependence to identify the most efficient copula model, which is used to construct a bivariate Weibull distribution for bivariate Survival times, among some Archimedean copulas is explored. Furthermore, to evaluate the efficiency of the proposed procedure, a simulation study is implemented. It is shown that this approach is useful for practical situations and applicable fo

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Publication Date
Mon Mar 01 2004
Journal Name
Al-academy
تقييم قابلية اداء متطلبات العمل للعاملين في الصناعة باستخدام طريقة القصور الذاتي
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تقييم قابلية اداء متطلبات العمل للعاملين في الصناعة باستخدام طريقة القصور الذاتي

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Publication Date
Wed Oct 24 2018
Journal Name
Journal Of Planner And Development
تقويم الآليات المقترحه لتنمية محافظة الانبار لسنة 2030 باستخدام اسلوب التحليل الهرمي
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Publication Date
Fri Jan 04 2019
Journal Name
Journal Of Planner And Development
نمذجة توزيع المدارس الابتدائية في مدينة الفلوجة باستخدام نظم المعلومات الجغرافية G.I.S
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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