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.
Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil
... Show MoreAny software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects
... Show MoreBiometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
... Show MoreTiO2 thin films were deposited by Spray Pyrolysis with thickness ((350±25) nm) onto glass substrates at (350°C), and the film was annealed at temperatures (400 and 500)°C. The structural and morphological properties of the thin films (TiO2) were investigated by X-ray diffraction, Field emission scanning electron microscopy and atomic force microscope. The gas sensor fabricated by evaporating aluminum electrodes using the annealed TiO2 thin films as an active material. The sensitivity of the sensors was determined by change the electrical resistance towards NO2 at different working temperatures (200
A submoduleA of amodule M is said to be strongly pure , if for each finite subset {ai} in A , (equivalently, for each a ?A) there exists ahomomorphism f : M ?A such that f(ai) = ai, ?i(f(a)=a).A module M is said to be strongly F–regular if each submodule of M is strongly pure .The main purpose of this paper is to develop the properties of strongly F–regular modules and study modules with the property that the intersection of any two strongly pure submodules is strongly pure .
Color image compression is a good way to encode digital images by decreasing the number of bits wanted to supply the image. The main objective is to reduce storage space, reduce transportation costs and maintain good quality. In current research work, a simple effective methodology is proposed for the purpose of compressing color art digital images and obtaining a low bit rate by compressing the matrix resulting from the scalar quantization process (reducing the number of bits from 24 to 8 bits) using displacement coding and then compressing the remainder using the Mabel ZF algorithm Welch LZW. The proposed methodology maintains the quality of the reconstructed image. Macroscopic and
This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of th
... Show MoreElbow stiffness is hard to treat and commonly resulted from trauma or degenerative arthritis. This study aimed to demonstrate the effectiveness of using ultrasound therapy in management of stiff elbow joint resulted from several etiological factors. A total number of 42 patients (35 male and 7 female) allocated randomly from the Department of Physiotherapy at Al-yarmouk Teaching Hospital during 2013. Each patient examined physically by physiotherapist taking in consideration the measurement of the joint movement angle using goniometer in flexion and the extension, and the pain score using visual analogue scale (VAS). Ultrasound therapy initiated thrice weekly for two weeks. At the time of entry, the means degree of flexion and extension
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