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Design of an adaptive state feedback controller for a magnetic levitation system
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This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controller in terms of the operating point. The results of the simulation show that the operating point has significant effect on the performance of nonadaptive SFC, and this performance may degrade as the operating point deviates from the equilibrium point, while the ASFC achieves the required design specification for any operating point and outperforms the state feedback controller from this point of view.

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Photoacoustic Imaging for Tumor Detection: An in vitro Simulation Study
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Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

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Publication Date
Thu Jan 08 2026
Journal Name
International Journal Of Engineering & Technology
An integrated multi layers approach for detecting unknown malware behaviours
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Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
An Evolutionary Algorithm for Solving Academic Courses Timetable Scheduling Problem
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Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

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Publication Date
Sat Jul 09 2022
Journal Name
Wireless Communications And Mobile Computing
An Optimized Approach for Industrial IoT Based on Edge Computing
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The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

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Publication Date
Thu Aug 01 2024
Journal Name
Smart Agricultural Technology
Smart fertilizer technologies: An environmental impact assessment for sustainable agriculture
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The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut

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Publication Date
Tue Apr 18 2023
Journal Name
Corporate Reputation Review
The Absorptive Capacity of Knowledge as an Approach for Building Strategic Reliability in the Sponge Organizations/Small Organizations in Kirkuk Governorate as a Model
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Publication Date
Thu Jun 01 2023
Journal Name
Iraqi Journal Of Physics
Design and Analysis of the Hexagonal-Shaped Antenna with Multi-Band Feature for WLAN, WiMAX, and LTE Applications
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Developing and researching antenna designs are analogous to excavating in an undiscovered mine. This paper proposes a multi-band antenna with a new hexagonal ring shape, theoretically designed, developed, and analyzed using a CST before being manufactured. The antenna has undergone six changes to provide the best performance. The results of the surface current distribution and the electric field distribution on the surface of the hexagonal patch were theoretically analyzed and studied. The sequential approach taken to determine the most effective design is logical, and prevents deviation from the work direction. After comparing the six theoretical results, the fifth model proved to be the best for making a prototype. Measured results rep

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
An efficient of Sansevieriatrifasciataplantas biosorbent for the treatment of metal contaminated industrial effluents
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Sansevieriatrifasciata was studied as a potential biosorbent for chromium, copper and nickel removal in batch process from electroplating and tannery effluents. Different parameters influencing the biosorption process such as pH, contact time, and amount of biosorbent were optimized while using the 80 mm sized particles of the biosorbent. As high as 91.3 % Ni and 92.7 % Cu were removed at pH of 6 and 4.5 respectively, while optimum Cr removal of 91.34 % from electroplating and 94.6 % from tannery effluents was found at pH 6.0 and 4.0 respectively. Pseudo second order model was found to best fit the kinetic data for all the metals as evidenced by their greater R2 values. FTIR characterization of biosorbent revealed the presence of carboxyl a

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Controlling the Unbalanced Voltages of a Series-Connected Lead-Acid Batteries in a PV Power Storage System using Dynamic Capacitor Technique
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Lead-acid batteries have been used increasingly in recent years in solar power systems, especially in homes and small businesses, due to their cheapness and advanced development in manufacturing them. However, these batteries have low voltages and low capacities, to increase voltage and capacities, they need to be connected in series and parallel. Whether they are connected in series or parallel, their voltages and capacities must be equal otherwise the quality of service will be degraded. The fact that these different voltages are inherent in their manufacturing, but these unbalanced voltages can be controlled. Using a switched capacitor is a method that was used in many methods for balancing voltages, but their respons

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