Majid Nour

King Abdulaziz University

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i-10 index

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Kemal Polat

Bolu Abant İzzet Baysal University

Hatem F. Sindi

King Abdulaziz University

Adi Alhudhaif

Prince Sattam Bin Abdulaziz University

Kourosh Kalantar‐zadeh

UNSW Sydney

Fayadh Alenezi

Al Jouf University

Muhyaddin Rawa

King Abdulaziz University

Kyle J. Berean

AgriBio

Ahmad Sabirin Zoolfakar

Universiti Teknologi MARA

ŞÖ

Şaban Öztürk

Selçuk University

Jian Zhen Ou

Southwest Jiaotong University

Cooperative Institutions

RMIT University

National University of Malaysia

MIT University

Universiti Teknologi MARA

King Abdulaziz University

National Institutes of Biotechnology Malaysia

RMIT Europe

University of Hassan II Casablanca

Commonwealth Scientific and Industrial Research Organisation

Jeddah University

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Silver nanoparticle/PDMS nanocomposite catalytic membranes for H2S gas removal

Journal of Membrane Science (2014)

Majid Nour Kyle J. Berean Adam F. Chrimes Ahmad Sabirin Zoolfakar Kay Latham

Polydimethylsiloxane

10.1016/j.memsci.2014.07.047

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Citations (39)

The Effect of Training and Testing Process on Machine Learning in Biomedical Datasets

Mathematical Problems in Engineering (2020)

Muhammed Kürşad Uçar Majid Nour Hatem F. Sindi Kemal Polat

Training and testing process for the classification of biomedical datasets in machine learning is very important. The researcher should choose carefully the methods that should be used at every step. However, there are very few studies on method choices. The studies in the literature are generally theoretical. Besides, there is no useful model for how to select samples in the training and testing process. Therefore, there is a need for resources in machine learning that discuss the training and testing process in detail and offer new recommendations. This article provides a detailed analysis of the training and testing process in machine learning. The article has the following sections. The third section describes how to prepare the datasets. Four balanced datasets were used for the application. The fourth section describes the rate and how to select samples at the training and testing stage. The fundamental sampling theorem is the subject of statistics. It shows how to select samples. In this article, it has been proposed to use sampling methods in machine learning training and testing process. The fourth section covers the theoretic expression of four different sampling theorems. Besides, the results section has the results of the performance of sampling theorems. The fifth section describes the methods by which training and pretest features can be selected. In the study, three different classifiers control the performance. The results section describes how the results should be analyzed. Additionally, this article proposes performance evaluation methods to evaluate its results. This article examines the effect of the training and testing process on performance in machine learning in detail and proposes the use of sampling theorems for the training and testing process. According to the results, datasets, feature selection algorithms, classifiers, training, and test ratio are the criteria that directly affect performance. However, the methods of selecting samples at the training and testing stages are vital for the system to work correctly. In order to design a stable system, it is recommended that samples should be selected with a stratified systematic sampling theorem.

Section (typography)

10.1155/2020/2836236

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Citations (117)

Determination of the pH sensitivity level of anodized Ta₂O₅ nanotubular using pH buffer solution: Towards engine oil deterioration sensor

Nur Lili Suraya Ngadiman Rozina Abdul Rani Zulasyraf Farhan Zulkifli Muhammad Firdaus Abdullah Siti Rabizah Makhsin

Tantalum is a potential material for metal anodizing, which enables the fabrication of ideal nanostructured Ta 2 O 5 . This project planned to employ Ta 2 O 5 , an anodized metal oxide, as a chemical sensor application. In the field of Ta 2 O 5 research, there is a lack of investigation into Ta 2 O 5 efficacy for the detection of engine oil deterioration. In this project, the objective is to fabricate Ta 2 O 5 nanotubular as sensing layers for the detection of engine oil deterioration. The Ta 2 O 5 sensor was fabricated through the anodization synthesis method and was then tested with 2, 4, 7, 10, and 12 pH buffer solutions. Anodization is very reliable for building nanostructures as it is easy to be manipulated. Samples were characterized using field emission scanning electron microscope (FESEM) for surface morphology and structural analysis, and their crystalline properties by X-ray diffraction (XRD). The output voltage was plotted over time, and the pH sensitivity of anodized Ta 2 O 5 was reported. As the result, the sensitivity sensor obtained for both 30 min and 60 min anodized samples were 31.616 mV/pH and 24.591 mV/pH, respectively, while the response time was obtained for rise time and fall time was 20 seconds and 90 seconds, respectively.

10.1109/rsm52397.2021.9511581

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Citations (2)

Parametric Analysis of an Optical Log-Spiral Nano-Antenna for Infrared Energy Harvesting

The Applied Computational Electromagnetics Society Journal (ACES) (2020)

Abdulrahman Alhomrani Ali Yahyaoui Anas Hashmi Ameni Mersani Majid Nour

In this paper, we present the design of a spiral nano-antenna dedicated to infrared energy harvesting at 28.3 THz. A comprehensive, detailed parametric study of key parameters such as the initial angle at the origin arm, width of the spiral arms, gap between the two arms, thickness of substrate, length of substrate, thickness of patch and number of turns of the nano-antenna is also presented and discussed in order to harvest maximum electric field in the gap of the spiral antenna in the frequency range of 28 – 29 THz. The maximum electric field is simulated at 28.1, 28.3, 28.5 and 28.7 THz. A variation of the electric field of the antenna for different value of incident wave angle at the resonance frequency 28.3 THz has been simulated. The main advantages of the studied structure are its ability to reach high confined electric field within its gap, its wideband behavior around the operating frequency 28.3 THz, and its insensitivity to polarization of incident electromagnetic waves.

Spiral antenna

Frequency band

10.47037/2020.aces.j.351011

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Citations (0)

A novel classification framework using multiple bandwidth method with optimized CNN for brain–computer interfaces with EEG-fNIRS signals

Neural Computing and Applications (2021)

Majid Nour Şaban Öztürk Kemal Polat

Interface (matter)

10.1007/s00521-021-06202-4

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Citations (25)

A Novel Approach to Skin Lesion Segmentation: Multipath Fusion Model with Fusion Loss

Computational and Mathematical Methods in Medicine (2022)

Adi Alhudhaif Hakan Öcal Necaattin Barışçı İsmail Atacak Majid Nour

Segmentation of skin lesions plays a very important role in the early detection of skin cancer. However, indistinguishability due to various artifacts such as hair and contrast between normal skin and lesioned skin is an important challenge for specialist dermatologists. Computer-aided diagnostic systems using deep convolutional neural networks are gaining importance in order to cope with difficulties. This study focuses on deep learning-based fusion networks and fusion loss functions. For the automatic segmentation of skin lesions, U-Net (U-Net + ResNet 2D) with 2D residual blocks and 2D volumetric convolutional neural networks were fused for the first time in this study. Also, a new fusion loss function is proposed by combining Dice Loss (DL) and Focal Tversky Loss (FTL) to make the proposed fused model more robust. Of the 2594 image dataset, 20% is reserved for test data and 80% for training data. In test data training, a Jaccard score of 0.837 and a dice score of 0.918 were obtained. The proposed model was also scored on the ISIC 2018 Task 1 test images, whose ground truths were not shared. The proposed model performed well and achieved a Jaccard index of 0.800 and a dice score of 0.880 in the ISIC 2018 Task 1 test set. In addition, it has been observed that the new fused loss function obtained by fusing Focal Tversky Loss and Dice Loss functions in the proposed model increases the robustness of the model in the tests. The proposed new loss function fusion model has outstripped the cutting-edge approaches in the literature.

Jaccard index

Dice

Robustness

Sørensen–Dice coefficient

10.1155/2022/2157322

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Citations (5)

A smart decision support system to diagnose arrhythymia using ensembled ConvNet and ConvNet-LSTM model

Expert Systems with Applications (2022)

Shamik Tiwari Anurag Jain Varun Sapra Deepika Koundal Fayadh Alenezi

Heart beat

10.1016/j.eswa.2022.118933

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Citations (42)

Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection

Computational and Mathematical Methods in Medicine (2022)

Majid Nour Derya Kandaz Muhammed Kürşad Uçar Kemal Polat Adi Alhudhaif

Measurement and monitoring of blood pressure are of great importance for preventing diseases such as cardiovascular and stroke caused by hypertension. Therefore, there is a need for advanced artificial intelligence-based systolic and diastolic blood pressure systems with a new technological infrastructure with a noninvasive process. The study is aimed at determining the minimum ECG time required for calculating systolic and diastolic blood pressure based on the Electrocardiography (ECG) signal.

SIGNAL (programming language)

10.1155/2022/5714454

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Citations (4)

Nanocomposite carbon-PDMS membranes for gas separation

Sensors and Actuators B Chemical (2011)

Majid Nour Kyle J. Berean Matthew Griffin Glenn I. Matthews Madhu Bhaskaran

Polydimethylsiloxane

10.1016/j.snb.2011.11.079

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Citations (67)

In vitro antioxidant activity of Ficus carica L. latex from 18 different cultivars

Scientific Reports (2020)

M. Shahinuzzaman Zahira Yaakob Farah Hannan Anuar Parul Akhtar Nurul Huda Abd Kadir

Abstract As synthetic antioxidants that are widely used in foods are known to cause detrimental health effects, studies on natural additives as potential antioxidants are becoming increasingly important. In this work, the total phenolic content (TPC) and antioxidant activity of Ficus carica Linn latex from 18 cultivars were investigated. The TPC of latex was calculated using the Folin–Ciocalteu assay. 1,1-Diphenyl-2-picrylhydrazyl (DPPH), 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and ferric ion reducing antioxidant power (FRAP) were used for antioxidant activity assessment. The bioactive compounds from F. carica latex were extracted via maceration and ultrasound-assisted extraction (UAE) with 75% ethanol as solvent. Under the same extraction conditions, the latex of cultivar ‘White Genoa’ showed the highest antioxidant activity of 65.91% ± 1.73% and 61.07% ± 1.65% in DPPH, 98.96% ± 1.06% and 83.04% ± 2.16% in ABTS, and 27.08 ± 0.34 and 24.94 ± 0.84 mg TE/g latex in FRAP assay via maceration and UAE, respectively. The TPC of ‘White Genoa’ was 315.26 ± 6.14 and 298.52 ± 9.20 µg GAE/mL via the two extraction methods, respectively. The overall results of this work showed that F. carica latex is a potential natural source of antioxidants. This finding is useful for further advancements in the fields of food supplements, food additives and drug synthesis in the future.

Carica

Maceration (sewage)

ABTS

Pomace

Ficus

10.1038/s41598-020-67765-1

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Citations (68)