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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay Kumar Sharma Mohammad Khalid Imam Rahmani Baijnath Kaushik Rania Almajalid Department of Computer science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia college of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in *** detection and effective treatment of BC can help save women’s *** an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection *** paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data *** novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated *** analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

Influence of cerium ions on structure-dependent magnetic properties of Ba-Sr M-type hexaferrite nanocrystals

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Journal of Rare Earths 2024年第2期42卷 364-372,I0005页

作者： Ram A.Pawar Sunil M.Patange P.M.Dighe Sher Singh Meena Abdullah GAl-Sehemi Mehboobali Pannipara Santosh S.Jadhav Department of Physics ArtsCommerce and Science CollegeAhmednagar413711MaharashtraIndia Department of Physics Shri Krishna MahavidyalayaGunjotiDistOsmanabad413606MaharashtraIndia Padmashri Vikhe Patil college of Arts Science and CommercePravaranagarA/P.Loni(Kd)Tal.RahataDistAhmednagar413713MaharashtraIndia Solid State Physics Division Bhabha Atomic Research CentreMumbai400085MaharashtraIndia Department of Chemistry King Khalid UniversityAbha61413Saudi Arabia Department of Physics D.S.M's ArtsCommerce and Science CollegeJintur431509MaharashtraIndia

The present study is a systematic effort to investigate the structure-sensitive magnetic parameters of Ce^(3+) substituted Ba-Sr hexaferrite nanocrystals chemically formulated as Ba_(0.5)Sr_(0.5)Ce_(x)Fe_(12-x)O_(19) where x=0.0-0.2 with Δx=*** hexaferrite powders were prepared using the sol-gel self-ignition route and structurally characterized by means of powder X-ray diffraction and Fourier transform infrared *** creation of the M-type hexaferrite phase within the synthesized samples was revealed from the Rietveld refinement of the X-ray *** occurrence of a secondary phase of CeO_(2) was revealed within the hexaferrites for the substitution,x> *** refined X-ray diffraction data were utilized to compute the lattice parameters,X-ray density,and lattice parameter *** crystal structure plotted from the refined XRD data reveals the occupancy of the ions at different lattice *** XPS data of the hexaferrite were analyzed to confirm the oxidation states of the constituent *** nanocrystalline nature of the hexaferrites was revealed from the crystallite sizes calculated using Scherer's *** analysis of FTIR spectra confirms that only a fraction of Ce^(3+)accommodated in the lattice and the remaining Ce content reside in the form of the CeO_(2) *** morphology of the hexaferrites was analyzed from the FESEM profiles of the ferrite *** magnetic behavior study was performed by analyzing the Curie temperature,hysteresis loops,and hyperfine interactions by means of susceptibility,V.S.M,and Mossbauer spectroscopy,*** hexaferrites with increasing coercivity,decreasing saturation magnetization,and decreasing Curie temperature are reported in the *** substituted Ce^(3+)ions inhibit the grain growth and create lattice imperfections giving rise to hexaferrites with tuned magnetic parameters suitable for different applications.

关键词： Ba-Sr hexaferrite Ce^(3+)substitution XPS Saturation magnetization Coercivity M?ssbauer spectroscopy

MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

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Computers, Materials & Continua 2024年第3期78卷 3489-3510页

作者： Rashmi Sharma Ashok Pal Nitin Mittal Lalit Kumar Sreypov Van Yunyoung Nam Mohamed Abouhawwash Department of Mathematics Chandigarh UniversityGharuanMohali140413India Deaprtment of Industry 4.0 Shri Vishwakarma Skill UniversityPalwal121102India Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Computational Mathematics Science and Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI 48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated *** uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective *** hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge *** evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been *** proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and *** primary objective of developing this hybrid approach has been achieved *** proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

关键词： Multi-objective optimization genetic algorithm ant lion optimizer metaheuristic

Strontium Thiogallate: An Efficient Green Emitting Phosphor for UV LEDs

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Journal of Applied Mathematics and Physics 2018年第4期6卷 663-666页

作者： N. D. Meshram P. J. Yadav Kamla Nehru Mahavidyalaya Sakkardara Nagpur India shri mathuradas mohota college of science Sakkardara India

In this paper we have reported green emission for europium activated strontium thiogallate. The phosphor is prepared by the precipitation method followed by heating at reducing atmosphere produced by the burning charcoal and characterized using XRD, PL and EL techniques. The phosphor SrGa2S4:Eu2+ gives intense green emission at 525 nm when excited by 400 nm wavelength. LEDs were also fabricated by coating europium activated strontium thiogallate on 390 nm LED chip. Intense green LEDs were obtained which can be useful for new LED applications. This phosphor can also be a prominent green component for the fabrication of white LEDs from UV diodes.

关键词： Luminescence Thiogallate SSL UV LED etc.

Phosphor Converted White Led with Improved CRI

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Journal of Applied Mathematics and Physics 2018年第4期6卷 657-662页

作者： P. J. Yadav N. D. Meshram C. P. Joshi S. V. Moharil Kamla Nehru Mahavidyalaya Sakkardara Nagpur India shri mathuradas mohota college of science Sakkardara Nagpur India Physics Department Shri Ramdeobaba K. N. Engineering College Nagpur India Department of Physics R.T.M. Nagpur University Nagpur India

Most of the commercial white LED lamps use blue chip coated with yellow emitting phosphor. YAG:Ce3+ phosphor is coated on blue chip to obtain white light. Though this is commercially successful, there are several drawbacks such as “halo effect”, poor colour rendition, etc. In recent years several efforts have been made to improve LED lamp performance. In this paper modifica-tion of YAG:Ce phosphor for improving CRI, by introducing Gd3+, Pr3+ or Tb3+ at Ce3+ site is reported.

关键词： YAG Phosphors White LED CRI and Commercial Phosphor etc.

Size Dependent Physical Properties of Nanostructured α-Fe_2O_3 Thin Films Grown by Successive Ionic Layer Adsorption and Reaction Method for Antibacterial Application

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Journal of Materials science & Technology 2015年第1期31卷 1-9页

作者： A.U.Ubale M.R.Belkhedkar Nanostructured Thin Film Materials Laboratory Department of PhysicsGovt.Vidarbha Institute of Science and Humanities Department of Physics Shri Shivaji College

Thin films of nanostructured α-FeOwith thickness of 1 56,203 and 251 nm were deposited by successive ionic layer adsorption and reaction(SILAR) method onto glass substrates using FeCl-6HO and NaOH as cationic and anionic *** X-ray diffraction studies revealed that,α-FeOthin films are nanocrystalline in nature with rhombohedral *** morphological properties were investigated by field emission scanning electron and atomic force *** optical studies showed that α-FeOexhibits direct as well as indirect optical band gap *** electrical resistivity of α-FeOat 305 K decreases from 11.76×102 to9.46 × 10~2 Ω cm as film thickness increases from 156 to 251 *** thermo-emf measurements confirmed that α-FeOexhibits n-type *** nanocrystalline α-FeOexhibits antibacterial character against Staphylococcus aureus and its efficiency increases from 37.50%to 87.50%depending on crystallite size.

关键词： Thin films Nanostructures AFM(atomic force microsc

Interpolation of Images Using Discrete Wavelet Transform to Simulate Image Resizing as in Human Vision

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International Journal of Automation and computing 2010年第1期7卷 9-16页

作者： Rohini S. Asamwar Kishor M. Bhurchandi Abhay S. Gandhi Department of Electronics and Communication Engineering Shri Ramdeobaba Kamla Nehru Engineering College Department of Electronics and Computer science Visvesvaraya National Institute of Technology

This paper presents discrete wavelet transform （DWT） and its inverse （IDWT） with Haar wavelets as tools to compute the variable size interpolated versions of an image at optimum computational load. As a human observer moves closer to or farther from a scene, the retinal image of the scene zooms in or out, respectively. This zooming in or out can be modeled using variable scale interpolation. The paper proposes a novel way of applying DWT and IDWT in a piecewise manner by non-uniform down- or up-sampling of the images to achieve partially sampled versions of the images. The partially sampled versions are then aggregated to achieve the final variable scale interpolated images. The non-uniform down- or up-sampling here is a function of the required scale of interpolation. Appropriate zero padding is used to make the images suitable for the required non-uniform sampling and the subsequent interpolation to the required scale. The concept of zeroeth level DWT is introduced here, which works as the basis for interpolating the images to achieve bigger size than the original one. The main emphasis here is on the computation of variable size images at less computational load, without compromise of quality of images. The interpolated images to different sizes and the reconstructed images are benchmarked using the statistical parameters and visual comparison. It has been found that the proposed approach performs better as compared to bilinear and bicubic interpolation techniques.

关键词： Discrete wavelet transform nomuniform sampling zeroeth level discrete wavelet transform (DWT) interpolation human vision.

Development of Efficient Classification Systems for the Diagnosis of Melanoma

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Computer Systems science & Engineering 2022年第7期42卷 361-371页

作者： S.Palpandi T.Meeradevi Department of Computer science and Engineering Shri Andal Alagar College of EngineeringChengalpet603111Tamil NaduIndia Department of Electronics and Communication Engineering Kongu Engineering CollegePerundurai638060ErodeTamil NaduIndia

Skin cancer is usually classiﬁed as melanoma and *** now represents 75%of humans passing away worldwide and is one of the most brutal types of ***,studies were not mainly focused on feature extraction of Melanoma,which caused the classiﬁcation ***,in this work,Histograms of orientation gradients and local binary pat-terns feature extraction procedures are used to extract the important features such as asymmetry,symmetry,boundary irregularity,color,diameter,etc.,and are removed from both melanoma and non-melanoma *** proposed Efﬁ-cient Classiﬁcation Systems for the Diagnosis of Melanoma(ECSDM)framework consists of different schemes such as preprocessing,segmentation,feature extrac-tion,and classiﬁ*** used Machine Learning(ML)and Deep Learning(DL)classiﬁers in the classiﬁcation *** ML classiﬁer is Naïve Bayes(NB)and Support Vector Machines(SVM).And also,DL classiﬁcation frame-work of the Convolution Neural Network(CNN)is used to classify the melanoma and benign *** results show that the Neural Network(NNET)classiﬁer’achieves 97.17%of accuracy when contrasting with ML classiﬁers.

关键词： Melanoma benign classiﬁcation systems performance parameters

Performance Evaluation of Deep Dense Layer Neural Network for Diabetes Prediction

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Computers, Materials & Continua 2023年第7期76卷 347-366页

作者： Niharika Gupta Baijnath Kaushik Mohammad Khalid Imam Rahmani Saima Anwar Lashari Department of Computer science and Engineering Shri Mata Vaishno Devi UniversityKatraJ&KIndia college of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia

Diabetes is one of the fastest-growing human diseases worldwide and poses a significant threat to the population’s longer *** prediction of diabetes is crucial to taking precautionary steps to avoid or delay its *** this study,we proposed a Deep Dense Layer Neural Network(DDLNN)for diabetes prediction using a dataset with 768 instances and nine *** also applied a combination of classical machine learning(ML)algorithms and ensemble learning algorithms for the effective prediction of the *** classical ML algorithms used were Support Vector Machine(SVM),Logistic Regression(LR),Decision Tree(DT),K-Nearest Neighbor(KNN),and Naïve Bayes(NB).We also constructed ensemble models such as bagging(Random Forest)and boosting like AdaBoost and Extreme Gradient Boosting(XGBoost)to evaluate the performance of prediction *** proposed DDLNN model and ensemble learning models were trained and tested using hyperparameter tuning and K-Fold cross-validation to determine the best parameters for predicting the *** combined ML models used majority voting to select the best outcomes among the *** efficacy of the proposed and other models was evaluated for effective diabetes *** investigation concluded that the proposed model,after hyperparameter tuning,outperformed other learning models with an accuracy of 84.42%,a precision of 85.12%,a recall rate of 65.40%,and a specificity of 94.11%.

关键词： Diabetes prediction hyperparameter tuning k-fold validation machine learning neural network

A review on anti-bacterials to combat resistance: From ancient era of plants and metals to present and future perspectives of green nano technological combinations

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Asian Journal of Pharmaceutical sciences 2020年第1期15卷 42-59页

作者： Lakshmi Kalyani Ruddaraju Sri Venkata Narayana Pammi Girija sankar Guntuku Veerabhadra Swamy Padavala Venkata Ramana Murthy Kolapalli Department of Pharmaceutics Shri Vishnu College of PharmacyBhimauaram 534202India Department of Materials science and Engineering Chungnam National UniversityRepublic of Korea A.U.college of Pharmaceutical sciences Visakhapatnam 530003India

In the primitive era, humans benefited partially from plants and metals to treat microbial infections. Later these infections were cured with antibiotics but further suffered from resistance issues. In searching of an alternative, researchers developed an adjuvant therapy but were hampered by spreading resistance. Subsequently, nanoparticles(NPs) were proposed to cease the multi-drug resistant bacteria but were hindered due to toxicity issues. Recently, a novel adjuvant therapy employed metals and botanicals into innovative nanotechnology as nano-antibiotics. The combination of green synthesized metallic NPs with antibiotics seems to be a viable platform to combat against MDR bacteria by alleviating resistance and toxicity. This review focuses on the primitive to present era dealings with bacterial resistance mechanisms, newer innovations of nanotechnology and their multiple mechanisms to combat resistance. In addition, special focus is paid on greener NPs as antibiotic carriers, and their future prospects of controlled release and toxicity study.

关键词： Antibiotics Bacterial resistance Green nanotechnology Adjuvant therapy Toxicity