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Finite Time Disturbance Observer Based on Air Conditioning System Control Scheme
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A novel robust finite time disturbance observer (RFTDO) based on an independent output-finite time composite control (FTCC) scheme is proposed for an air conditioning-system temperature and humidity regulation. The variable air volume (VAV) of the system is represented by two first-order mathematical models for the temperature and humidity dynamics. In the temperature loop dynamics, a RFTDO temperature (RFTDO-T) and an FTCC temperature (FTCC-T) are designed to estimate and reject the lumped disturbances of the temperature subsystem. In the humidity loop, a robust output of the FTCC humidity (FTCC-H) and RFTDO humidity (RFTDO-H) are also designed to estimate and reject the lumped disturbances of the humidity subsystem. Based on Lyapunov theory, the stability proof of the two closed-loop controllers and observers is presented. Comparative simulations are carried out to confirm that the proposed controller outperforms conventional methods and offers greater accuracy of temperature, humidity, and carbon dioxide concentration, having superior regulation performance in terms of a rapid finite time convergence, an outstanding disturbance rejection property, and better energy consumption. In addition to presenting the comparative simulation results from the control applications on the VAV system, the quantitative values are provided to further confirm the superiority of the proposed controller. In particular, the proposed method exhibits the shortest settling time of, respectively, 15 and 40 min to reach the expected temperature and humidity, whereas other comparative controllers require a longer time to settle down.

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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
The Importance and Interaction Indices of Bi-Capacities Based on Ternary-Element Sets
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Grabisch and Labreuche have recently proposed a generalization of capacities, called the bi-capacities. Recently, a new approach for studying bi-capacities through introducing a notion of ternary-element sets proposed by the author. In this paper, we propose many results such as bipolar Mobius transform, importance index, and interaction index of bi-capacities based on our approach.

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Publication Date
Mon Jun 01 2020
Journal Name
Sensing And Bio-sensing Research
Hydrogen peroxide biosensor based on hemoglobin-modified gold nanoparticles–screen printed carbon electrode
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Publication Date
Sun Nov 19 2017
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Image Compression based on Fixed Predictor Multiresolution Thresholding of Linear Polynomial Nearlossless Techniques
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Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

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Publication Date
Mon Oct 19 2026
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Tue Dec 01 2020
Journal Name
Minar International Journal Of Applied Sciences And Technology
INNOVATE GESTATIONAL AGE ESTIMATION MODEL FOR IRAQI FETUSES BASED ON ULTRASOUND IMAGES MEASUREMENTS
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Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo

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Publication Date
Thu Jun 06 2024
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG)
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Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Publication Date
Mon Dec 03 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Condition assessment and rehabilitation for trunk sewer deterioration based on Semi-Markov model
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An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

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Publication Date
Thu Jan 01 2026
Journal Name
Ieee Access
SD-GPON: A Dynamic Prioritization for Efficient Traffic Management Based on Controlling DSCP
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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Advanced Research
UV Photovoltaic detector based on Bi doped TiO2 Fabricated by Pulse Laser Deposition
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Pure and doped TiO 2 with Bi films are obtained by pulse laser deposition technique at RT under vacume 10-3 mbar, and the influence of Bi content on the photocvoltaic properties of TiO 2 hetrojunctions is studied. All the films display photovoltaic in the near visible region. A broad double peaks are observed around λ= 300nm for pure TiO 2 at RT in the spectral response of the photocurrent, which corresponds approximately to the absorption edge and this peak shift to higher wavelength (600 nm) when Bi content increase by 7% then decrease by 9%. The result is confirmed with the decreasing of the energy gap in optical properties. Also, the increasing is due to an increase in the amount of Bi content, and shifted to 400nm when annealed at 523

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