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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 Bayesian classifier (NBC) have been enhanced as compared to the dataset before applying the proposed method. Moreover, the results indicated that issa was performed better than the statistical imputation techniques such as deleting the samples with missing values, replacing the missing values with zeros, mean, or random values.

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images
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A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

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Publication Date
Thu Sep 01 2022
Journal Name
Brazilian Journal Of Chemical Engineering
A computational study on the potential application of Ca12O12 cluster for sensing of fungicide molecule
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Density functional theory calculations are employed to investigate the impact of edifenphos molecule on the reactivity and electronic sensitivity of pure calcium oxide (CaO) nanocluster. The strong adsorption of edifenphos molecule on CaO nanocluster occurs by the sulfur head of the adsorbate, and the amount of the energy of this adsorption is around − 84.40 kcal/mol. The adsorption of edifenphos molecules results in a decrease in the values of Eg of CaO from 4.67 to 3.56 eV, as well as an increase in the electrical conductance. Moreover, the work function of CaO nanocluster is significantly affected, which changes the current of the field emission electron. Eventually, the recovery time is calculated around 99 ms at ambient temperature f

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
Highly Sensitive Fiber Brag Grating Based Gas Sensor Integrating Polyaniline Nanofiber for Remote Monitoring
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Publication Date
Thu Apr 06 2017
Journal Name
Chalcogenide Letters
CdS/PMMA-based inorganic/organic heterojunction for H<sub>2</sub>S gas sensing
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The performance of H2S sensor based on poly methyl methacrylate (PMMA)-CdS nanocomposite fabricated by spray pyrolysis technique has been reported. XRD pattern diffraction peaks of nano CdS has been indexed to the hexagonally wurtzite structured The nanocomposite exhibits semiconducting behavior with optical energy gap of4.06eV.SEM morphology appears almost tubes like with CdS/PMMA network. That means the addition of CdS to polymer increases the roughness in the film and provides high surface to volume ratio, which helps gas molecule to adsorb on these tubes. The resistance of PMMA-CdS nanocomposite showed a considerable change when exposed to H2S gas. Fast response time to detect H2S gas was achieved by using PMMA-CdS thin film sensor. The

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
High Order Sliding Mode Observer-Based Output Feedback Controller Design For Electro-Hydraulic System
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A perturbed linear system with property of strong observability ensures that there is a sliding mode observer to estimate the unknown form inputs together with states estimation. In the case of the electro-hydraulic system with piston position measured output, the above property is not met. In this paper, the output and its derivatives estimation were used to build a dynamic structure that satisfy the condition of strongly observable. A high order sliding mode observer (HOSMO) was used to estimate both the resulting unknown perturbation term and the output derivatives. Thereafter with one signal from the whole system (piton position), the piston position make tracking to desire one with a simple linear output feedback controller after ca

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Publication Date
Thu Jan 13 2022
Journal Name
Medical &amp; Biological Engineering &amp; Computing
An integrated entropy-spatial framework for automatic gender recognition enhancement of emotion-based EEGs
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

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Publication Date
Fri Dec 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Airborne Computer System Based Collision-Free Flight Path Finding Strategy Design for Drone Model
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Publication Date
Fri Jul 01 2022
Journal Name
Optical Fiber Technology
Highly sensitive fiber Bragg grating based gas sensor integrating polyaniline nanofiber for remote monitoring
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