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Applying Cognitive Methodology in Designing On-Line Auto-Tuning Robust PID Controller for the Real Heating System
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A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA). Matlab simulation package is used to carry out the proposed methodology that finds and tunes the optimal values of the robust PID parameters on-line. In real-time, the LabVIEW package is guided to design the on-line robust PID controller for the heating system. Numerical simulations and experimental results are compared with each other and showed the effectiveness of the proposed control methodology in terms of fast and smooth dynamic response for the heating system, especially when the control methodology considers the external disturbance attenuation problem.

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Global Pharma Technology
Modified ZnO for efficient photo-catalysis by Silver/Graphite oxide nanoparticles
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Design of L-Band Multiwavelength Laser for TDM/WDM PON Application
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This paper presents on the design of L-Band Multiwavelength laser for Hybrid Time Division Multiplexing/ Wavelength Division Multiplexing (TDM/WDM) Passive Optical Network (PON) application. In this design, an L-band Mulltiwavelength Laser is designed as the downstream signals for TDM/WDM PON. The downstream signals ranging from 1569.865 nm to 1581.973 nm with 100GHz spacing. The multiwavelength laser is designed using OptiSystem software and it is integrated into a TDM/WDM PON that is also designed using OptiSystem simulation software. By adapting multiwavelength fiber laser into a TDM/WDM network, a simple and low-cost downstream signal is proposed. From the simulation design, it is found that the proposed design is suitable to be used

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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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Publication Date
Sun Dec 25 2022
Journal Name
Nurse Media Journal Of Nursing
Targeting Smoking Triggers: A Nurse-led Intervention for Tobacco Smoking Cessation
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Background: Nursing interventions tailored to the smoking triggers in patients with non-communicable chronic diseases are essential. However, these interventions are scant due to the nature of factors associated with smoking cessation and the poor understanding of the effect of nurse-led intervention in Iraq.Purpose: This study aimed to determine the dominant smoking triggers and examine the effects of a tailored nursing intervention on smoking behavior in patients with non-communicable chronic diseases.Methods: Convenience samples of 128 patients with non-communicable chronic diseases, male and female patients, who were 18-70 years old, were recruited in this quasi-experimental, randomized comparative trial in the outpatient clinic

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Publication Date
Mon Mar 27 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Design, Synthesis, Characterization and Preliminary Anticancer Study for Methotrexate Silibinin Conjugates
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The spectrum of clinical efficacy of Methotrexate (MTX) is broad in that MTX is used in the treatment of certain cancers, severe psoriasis and rheumatoid arthritis.Various mechanisms by which cancer cells grown in tissue culture become resistant to anticancer drugs. The use of multiple  drugs with different mechanisms of entry into cells and different cellular targets allows for effective chemotherapy and high cure rates. In an efforts to develop effective strategies that increase the therapeutic potential of anticancer drugs with less systemic toxicity ,are being directed  towards the investigation of dietary supplements and other phytotherapeutic agents for their synergistic efficacy in combination with anticancer drugs. A pr

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Publication Date
Sun Dec 01 2019
Journal Name
Applied Soft Computing
A new evolutionary multi-objective community mining algorithm for signed networks
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Publication Date
Fri Mar 01 2024
Journal Name
Advances In Structural Engineering
Simulation and design model for reinforced concrete slabs with lacing systems
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Lacing reinforcement plays a critical role in the design and performance of reinforced concrete (RC) slabs by distributing the applied loads more evenly across the slab, ensuring that no specific area of the slab is overloaded. In this study, nine slabs, divided into three groups according to the investigated parameters, were meticulously designed and evaluated to study the interplay between the lacing reinforcement and other key parameters. Each slab was crafted for simple support and was subjected to both static and repeated two-point load tests. The lacing reinforcement had an angle of 45° with various tension and lacing steel. The repeated-tested specimens with lacing reinforcement experienced smaller ductility than those of s

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Publication Date
Fri Mar 01 2024
Journal Name
Advances In Structural Engineering
Simulation and design model for reinforced concrete slabs with lacing systems
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Lacing reinforcement plays a critical role in the design and performance of reinforced concrete (RC) slabs by distributing the applied loads more evenly across the slab, ensuring that no specific area of the slab is overloaded. In this study, nine slabs, divided into three groups according to the investigated parameters, were meticulously designed and evaluated to study the interplay between the lacing reinforcement and other key parameters. Each slab was crafted for simple support and was subjected to both static and repeated two-point load tests. The lacing reinforcement had an angle of 45° with various tension and lacing steel. The repeated-tested specimens with lacing reinforcement experienced smaller ductility than those of s

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
Wastewater Bio-solids Management for Fertilizer Quality Using Co- composting Process
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Co-composting process can be acquired by combining organic fraction of municipal solid waste (OFMSW) with sewage sludge (SS) and mature compost (MC) as enhancement and bulking agent to overcome the problems of municipal solid waste and wastewater treatment plants besides the finally produced fertilizer usage for agriculture and horticulture. The effects of different mixture ratios of (OFMSW), (SS) and (MC) on the performance of composting process were investigated in this study. Piles of about 10 kg were prepared by mixing OFMSW, SS and MC in three different ratios (w/w) [OFMSW: SS: MC= 3:1:1, 3:2:1, and 3:3:1]. Results showed that the pile [3:1:1] was most beneficial to composting. The final compost products contained a

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

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