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An Integrated Deep Learning Framework for Fruits Diseases Classification

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Computers, Materials & Continua 2022年第4期71卷 1387-1402页

作者： Abdul majid muhammad Attique Khan Majed Alhaisoni muhammad Asfand Eyar Usman Tariq Nazar hussain Yunyoung Nam Seifedine Kadry Department of Computer Science HITEC University TaxilaTaxilaPakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Department of Computer Science Bahria UniversityIslamabad College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway

:Agriculture has been an important research area in the field of image processing for the last five *** affect the quality and quantity of fruits,thereby disrupting the economy of a *** computerized techniques have been introduced for detecting and recognizing fruit ***,some issues remain to be addressed,such as irrelevant features and the dimensionality of feature vectors,which increase the computational time of the ***,we propose an integrated deep learning framework for classifying fruit *** consider seven types of fruits,i.e.,apple,cherry,blueberry,grapes,peach,citrus,and *** proposed method comprises several important ***,data increase is applied,and then two different types of features are *** the first feature type,texture and color features,i.e.,classical features,are *** the second type,deep learning characteristics are extracted using a pretrained *** pretrained model is reused through transfer ***,both types of features are merged using the maximum mean value of the serial ***,the resulting fused vector is optimized using a harmonic threshold-based genetic ***,the selected features are classified using multiple *** evaluation is performed on the PlantVillage dataset,and an accuracy of 99%is achieved.A comparison with recent techniques indicate the superiority of the proposed method.

关键词： Fruit diseases data augmentation deep learning classical features features fusion features selection

Fault Detection and Identification Using Deep Learning Algorithms in Induction Motors

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Computer Modeling in Engineering & Sciences 2022年第11期133卷 435-470页

作者： majid hussain Tayab Din Memon Imtiaz hussain Zubair Ahmed Memon Dileep Kumar Department of Electronic Engineering Quaid-e-Awam University of Engineering Science and TechnologyNawabshah67480Pakistan NCRA Condition Monitoring Systems Lab Mehran University of Engineering and TechnologyJamshoro76062Pakistan Department of Electronic Engineering Mehran University of Engineering and TechnologyJamshoro76062Pakistan Design and Creative Technology Torrens University AustraliaMelbourneAustralia Department of Electronics and Power Engineering Pakistan Navy Engineering College NUSTKarachi75350Pakistan

Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach to avoiding plant disturbances and ***,Motor Current Signature Analysis(MCSA)is widely reported as a condition monitoring technique in the detection and identification of individual andmultiple Induction Motor(IM)***,checking the fault detection and classification with deep learning models and its comparison among them selves or conventional approaches is rarely reported in the ***,in this work,wepresent the detection and identification of induction motor faults with MCSA and three Deep Learning(DL)models namely MLP,LSTM,and ***,we have developed the model of Squirrel Cage induction motor in MATLAB and simulated it for single phasing and stator winding faults(SWF)using Fast Fourier Transform(FFT),Short Time Fourier Transform(STFT),and Continuous Wavelet Transform(CWT)to detect and identify the healthy and unhealthy conditions with phase to ground,single phasing and in multiple fault conditions using Motor Current Signature *** faults impact on stator current is presented in the time and frequency domain(i.e.,power spectrum).The simulation results show that the scalogram has shown good results in time-frequency analysis for fault and showing its impact on the energy of current during individual fault and multiple fault *** is further investigated with three deep learning models(i.e.,MLP,LSTM,and 1D-CNN)for checking the fault detection and identification(i.e.,classification)improvement in a three-phase induction *** simulating the three-phase induction motor in various healthy and unhealthy conditions in MATLAB,we have collected current signature data in the time domain,labeled them accordingly and created the 50 thousand samples dataset for DL *** the DL models are trained and validated with a suitable number of architecture *** simulation,the multiclass confusion

关键词： Condition monitoring motor fault diagnosis stator winding faults deep learning signal processing

Novel Scheme for Robust Confusion Component Selection Based on Pythagorean Fuzzy Set

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Computers, Materials & Continua 2023年第3期74卷 6523-6534页

作者： Nabilah Abughazalah Mohsin Iqbal majid Khan Iqtadar hussain Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Mathematics&Statistics Riphah International UniversityIslamabadPakistan Department of Applied Mathematics&Statistics Institute of Space TechnologyIslamabadPakistan Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar Statistical Consulting Unit College of Arts and ScienceQatar UniversityDohaQatar

The substitution box,often known as an S-box,is a nonlinear component that is a part of several block *** purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults.A Multi-Criteria Decision Making(MCDM)problem has a complex selection procedure because of having many options and criteria to choose *** of this,statistical methods are necessary to assess the performance score of each S-box and decide which option is the best one available based on this *** the Pythagorean Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)method,the major objective of this investigation is to select the optimal S-box to be implemented from a pool of twelve key *** the help of the Pythagorean fuzzy set(PFS),the purpose of this article is to evaluate whether this nonlinear component is suitable for use in a variety of encryption *** this article,we have considered various characteristics of S-boxes,including nonlinearity,algebraic degree,strict avalanche criterion(SAC),absolute indicator,bit independent criterion(BIC),sum of square indicator,algebraic immunity,transparency order,robustness to differential cryptanalysis,composite algebraic immunity,signal to noise ratio-differential power attack(SNR-DPA),and confusion coefficient variance on some standard S-boxes that are Advanced Encryption Following this,the findings of the investigation are changed into Pythagorean fuzzy numbers in the shape of a *** matrix is then subjected to an analysis using the TOPSIS method,which is dependent on the Pythagorean fuzzy set,to rank the most suitable S-box for use in encryption applications.

关键词： Decision making substitution box TOPSIS multi-criterion decision making fuzzy set Pythagorean fuzzy set

Generalization of Advanced Encryption Standard Based on Field of Any Characteristic

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Computers, Materials & Continua 2022年第12期73卷 6121-6138页

作者： Nabilah Abughazalah majid Khan Noor Munir Ammar SAlanazi Iqtadar hussain Department of Mathematical Sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Applied Mathematics&Statistics Institute of Space TechnologyIslamabadPakistan King Abdulaziz City for Science and Technology RiyadhSaudi Arabia Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar Statistical Consulting Unit College of Arts and ScienceQatar UniversityDohaQatar

Nowadays most communications are done by utilizing digital transmission *** security of this digital information transmitted through different communication systems is quite *** secrecy of digital data is one of the burning topics of the digitally developed *** exist many traditional algorithms in the literature to provide methods for robust *** most important and recent modern block cipher named the advanced encryption standard(AES)is one of the extensively utilized encryption schemes with binary *** is a succession of four fundamental steps:round key,sub-byte,shift row,and mix *** this work,we will provide an innovative methodology for extending the AES in a Galois fieldwith any characteristic *** four steps in the fundamental process with binary characteristics will be adjusted because of the new *** applying double affine transformations,we have enhanced the number of options in our suggested substitution *** reconstruction of the nonlinear confusion component and encryption structure provides robustness in the generalized *** increase in the keyspace due to the Galois field generalization implies that we have improved additional confusion abilities and broadened the current *** implementation of the proposed structure of AES for image,audio,and video encryption will provide high security for secure communication.

关键词： AES generalized AES binary field ternary function

Atmospheric Convection Model Based Digital Confidentiality Scheme

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Computers, Materials & Continua 2022年第6期71卷 4503-4522页

作者： Noor Munir majid Khan Mohammad Mazyad Hazzazi Amer Aljaedi Sajjad Shaukat Jamal Iqtadar hussain Department of Applied Mathematics and Statistics Institute of Space TechnologyIslamabadPakistan Department of Mathematics College of ScienceKing Khalid UniversityAbha61413Saudi Arabia College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia Department of Mathematics Statistics and PhysicsQatar UniversityDoha2713Qatar

Nonlinear dynamics is a fascinating area that is intensely affecting a wide range of different disciplines of science and technology *** combination of different innovative topics of information security and high-speed computing has added new visions into the behavior of complex nonlinear dynamical systems which uncovered amazing results even in the least difficult *** generation of complex actions froma very simple dynamical method has a strong relation with information *** protection of digital content is one of the inescapable concerns of the digitally advanced ***,information plays an important role in everyday life and affects the surroundings *** digital contents consist of text,images,audio,and videos,*** to the vast usage of digital images in the number of social and web applications,its security is one of the biggest *** this work,we have offered an innovative image encryption technique based on present criteria of confusion and *** designed scheme comprises two major nonlinear dynamical *** have employed discrete fractional chaotic iterative maps to add confusion capability in our suggested algorithm and continuous chaotic Lorenz *** have verified our offered scheme by using statistical *** investigations under the statistical tests suggested that our proposed technique is quite reasonable for the security of digital data.

关键词： Lorenz atmospheric convection model fractional logistic map image encryption S-box

Classification of Nonlinear Confusion Component Using Hybrid Multi-Criteria Decision Making

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Intelligent Automation & Soft Computing 2023年第5期36卷 1451-1463页

作者： Nabilah Abughazalah Iqra Ishaque majid Khan Ammar S.Alanazi Iqtadar hussain Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Applied Mathematics and Statistics Institute of Space TechnologyIslamabadPakistan Department of Mathematics King Abdulaziz UniversityFaculty of ScienceJeddahSaudi Arabia Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar Statistical Consulting Unit College of Arts and ScienceQatar UniversityDohaQatar

In today’s digital world,the most inevitable challenge is the protection of digital *** to the weak conﬁdentiality preserving techniques,the existing world is facing several digital information *** make our digital data indecipherable to the unauthorized person,a technique forﬁnding a crypto-graphically strong Substitution box(S-box)have *** S-box with sound cryptographic assets such as nonlinearity(NL),strict avalanche criterion(SAC),bit independence criteria(BIC),bit independence criteria of nonlinearity(BIC-NL),Bit independence criteria of Strict avalanche criteria(BIC-SAC),and Input/output XOR is considered as the robust *** Decision-Making Trial and Evaluation Laboratory(DEMATEL)approach of multi-criteria decision making(MCDM)is proposed forﬁnding the interrelation among cryptographic properties.A combination of two MCDM methods namely Entropy and multi-objective optimization based on ratio analysis(MOORA)is applied for the best S-box selection.A robust substitution box is selected for secure communications in cryptography by using the combination of DEMETAL selection criteria,entro-py weight assigning,and MOORA ranking *** combination of these three methods provides a fast selection procedure for the secure confusion *** offered selection method can also be utilized for the choice of the best cryptosystem with highly secure properties and resistive against all possible linear and differential attacks in the cryptanalysis.

关键词： DEMATEL MCDM MOORA nonlinearity S-box

Enhancing Dielectric and Mechanical Behaviors of Hybrid Polymer Nanocomposites Based on Polystyrene,Polyaniline and Carbon Nanotubes Coated with Polyaniline

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Chinese Journal of Polymer Science 2016年第12期34卷 1500-1509页

作者： Tanveer ul Haq Zia Ahmad Nawaz Khan majid hussain Ibrar Hassan Iftikhar hussain Gul Department of Materials Engineering School of Chemical and Materials EngineeringNational University of Sciences and Technology

The dielectric and mechanical properties of hybrid polymer nanocomposites of polystyrene/polyaniline/carbon nanotubes coated with polyaniline （pCNTs） have been investigated using impedance analyzer and extensometer. The blends of PS/PANI formed the heterogeneous phase separated morphology in which pCNTs are dispersed uniformly. The incorporation of a small amount of pCNTs into the blend of PS/PANI has remarkably increased the dielectric properties. Similarly, the AC conductivity of PS/PANI is also increased five orders of magnitude from 1.6 × 10^-10 to 2.0×10^-5 ***-1 in the hybrid nanocomposites. Such behavior of hybrid nanocomposites is owing to the interfacial polarization occurring due to the presence of multicomponent domains with varying conductivity character of the phases from insulative PS to poor conductor PANI to highly conductive CNTs. Meanwhile, the tensile modulus and tensile strength are also enhanced significantly up to 55% and 160%, respectively, without much loss of ductility for three phase hybrid nanocomposites as compared to the neat PS. Thereby, the hybrid nanocomposites of PS/PANI/pCNTs become stiffer, stronger and tougher as compared to the neat systems.

关键词： Nanocomposites Carbon nanotubes Dielectric behavior Mechanical properties Polystyrene.

Classification of Positive COVID-19 CT Scans Using Deep Learning

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Computers, Materials & Continua 2021年第3期66卷 2923-2938页

作者： muhammad Attique Khan Nazar hussain Abdul majid Majed Alhaisoni Syed Ahmad Chan Bukhari Seifedine Kadry Yunyoung Nam Yu-Dong Zhang Department of Computer Science HITEC University TaxilaPakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Division of Computer Science Mathematics and ScienceCollins College of Professional StudiesSt.’John’s UniversityNew YorkUSA Department of Mathematics and Computer Science Beirut Arab UniversityLebanon Department of Computer Science and Engineering Soonchunhyang UniversityAsanSouth Korea Department of Informatics University of LeicesterLeicesterUK

In medical imaging,computer vision researchers are faced with a variety of features for verifying the authenticity of classifiers for an accurate *** response to the coronavirus 2019(COVID-19)pandemic,new testing procedures,medical treatments,and vaccines are being developed *** potential diagnostic tool is a reverse-transcription polymerase chain reaction(RT-PCR).RT-PCR,typically a time-consuming process,was less sensitive to COVID-19 recognition in the disease’s early *** we introduce an optimized deep learning(DL)scheme to distinguish COVID-19-infected patients from normal patients according to computed tomography(CT)*** the proposed method,contrast enhancement is used to improve the quality of the original images.A pretrained DenseNet-201 DL model is then trained using transfer *** fully connected layers and an average pool are used for feature *** extracted deep features are then optimized with a Firefly algorithm to select the most optimal learning *** the selected features is important to improving the accuracy of the approach;however,it directly affects the computational cost of the *** the proposed method,a new parallel high index technique is used to fuse two optimal vectors;the outcome is then passed on to an extreme learning machine for final *** were conducted on a collected database of patients using a 70:30 training:Testing *** results indicated an average classification accuracy of 94.76%with the proposed approach.A comparison of the outcomes to several other DL models demonstrated the effectiveness of our DL method for classifying COVID-19 based on CT scans.

关键词： Coronavirus contrast enhancement deep learning features optimization fusion classification

Spatial and Temporal Analyses of Water Quality in the Dhrabi Watershed of Pakistan： Issues and Options

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Journal of Environmental Science and Engineering(A) 2012年第3期1卷 329-340页

作者： muhammad Ashraf Theib Y. Oweis Abdur Razzaq Bashir hussain Abdul majid International Center for Agricultural Research in the Dry Areas （ICARDA） National Agricultural Research Centre lslamabad 44000 Pakistan International Center for Agricultural Research in the Dry Areas （ICARDA） Aleppo 15310 Syria Soil and Water Conservation Research Institute （SA WCRI） Chakwa148800 Pakistan

Monitoring water quality is important for maintaining a healthy watershed, but it is mostly ignored in watershed planning and management. In the Dhrabi watershed of Pakistan, the quality of surface water was monitored at 16 locations to assess suitability for irrigation over regular intervals during the period 2007-2010. Similarly, groundwater quality was monitored at 10 locations for drinking and irrigation purposes. There was high spatial and temporal variability in surface water quality. Electrical conductivity (EC) and residual sodium carbonate (RSC) either exceeded or fluctuated around permissible limits at most of the locations throughout the monitoring period. Therefore, the use of such water for irrigation needs special care, otherwise its prolonged use may pose soil salinity and sodicity problems. The trend of EC and RSC for groundwater was similar to that for surface water. Exchangeable Mg2+ exceeded permissible limits for most of the surface water and groundwater samples. In addition, microbial analysis of groundwater revealed that only two out of eight monitoring points during August 2009, none out of eight points during February 2010, and one out of nine points during June 2010 provided water fit for drinking. Soil samples were collected from the catchment areas of the major contributing streams and from the beds of the Kallar Kahar Lake and the Dhrabi Reservoir. The soil samples from the catchments showed high salinity and sodicity that may be the cause of high salinity and sodicity in the streams. The highest EC, sodium adsorption ratio (SAR) and exchangeable sodium percentage (ESP) in the bed samples from the Kallar Kahar Lake were about 43 dS/m, 56, and 45, respectively. These high values were due to the saline water brought into the lake with the runoff.

关键词：流域水质巴基斯坦时空分析土壤含盐量水库集水区选项水质监测环境质量监测