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Histogram-Based Decision Support System for Extraction and Classification of Leukemia in Blood Smear Images

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Computer Systems Science & Engineering 2023年第8期46卷 1879-1900页

作者： Neenavath veeraiah Youseef Alotaibi Ahmad FSubahi Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P.521180India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia

An abnormality that develops in white blood cells is called *** diagnosis of leukemia is made possible by microscopic investigation of the smear in the *** training is necessary to complete the morphological examination of the blood smear for leukemia *** paper proposes a Histogram Threshold Segmentation Classifier(HTsC)for a decision support *** proposed HTsC is evaluated based on the color and brightness variation in the dataset of blood smear *** operations are used to crop the nucleus based on automated *** Blood Cell(WBC)segmentation is calculated using the active contour model to determine the contrast between image regions using the color transfer *** entropy-adaptive mask generation,WBCs accurately detect the circularity region for identification of the *** proposed HTsC addressed the cytoplasm region based on variations in size and shape concerning addition and rotation *** in WBC imaging characteristics depends on the cytoplasmic and nuclear *** computation of the variation between image features in the cytoplasm and nuclei regions of the WBCs is used to classify blood smear *** classification of the blood smear is performed with conventional machine-learning techniques integrated with the features of the deep-learning regression *** designed HTsC classifier comprises the binary classifier with the classification of the lymphocytes,monocytes,neutrophils,eosinophils,and abnormalities in the *** proposed HTsC identifies the abnormal activity in the WBC,considering the color and shape *** exhibits a higher classification accuracy value of 99.6%when combined with the other *** comparative analysis expressed that the proposed HTsC model exhibits an overall accuracy value of 98%,which is approximately 3%–12%higher than the conventional technique.

关键词： White blood cells leukemia segmentation histogram blood smear

A Novel Gradient Boosted Energy Optimization Model(GBEOM)for MANET

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Computer Systems Science & Engineering 2023年第7期46卷 637-657页

作者： Neenavath veeraiah Youseef Alotaibi Saleh Alghamdi Satish Thatavarti Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P521180India Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramA.P522502India

Mobile Ad Hoc Network(MANET)is an infrastructure-less network that is comprised of a set of nodes that move *** MANET,the overall performance is improved through multipath multicast routing to achieve the quality of service(quality of service).In this,different nodes are involved in the information data collection and transmission to the destination nodes in the *** different nodes are combined and presented to achieve energy-efficient data transmission and classification of the *** route identification and routing are established based on the data broadcast by the network *** transmitting the data packet,evaluating the data delivery ratio is necessary to achieve optimal data transmission in the ***,energy consumption and overhead are considered essential factors for the effective data transmission rate and better data delivery *** this paper,a Gradient-Based Energy Optimization model(GBEOM)for the route in MANET is proposed to achieve an improved data delivery ***,the Weighted Multi-objective Cluster-based Spider Monkey Load Balancing(WMC-SMLB)technique is utilized for obtaining energy efficiency and load balancing *** WMC algorithm is applied to perform an efficient node clustering process from the considered mobile nodes in *** balancing efficiency is improved with a higher data delivery ratio and minimum routing overhead based on the residual energy and bandwidth ***,the Gradient Boosted Multinomial ID3 Classification algorithm is applied to improve the performance of multipath multicast routing in MANET with minimal energy consumption and higher load balancing *** proposed GBEOM exhibits∼4%improved performance in MANET routing.

关键词： Manet routing load balancing clustering gradient boosting

MayGAN:Mayfly Optimization with Generative Adversarial Network-Based Deep Learning Method to Classify Leukemia Form Blood Smear Images

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Computer Systems Science & Engineering 2023年第8期46卷 2039-2058页

作者： Neenavath veeraiah Youseef Alotaibi Ahmad F.Subahi Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P.521180India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia

Leukemia,often called blood cancer,is a disease that primarily affects white blood cells(WBCs),which harms a person’s tissues and *** condition may be fatal when if it is not diagnosed and recognized at an early *** physical technique and lab procedures for Leukaemia identification are considered *** is crucial to use a quick and unexpected way to identify different forms of *** screening of the morphologies of immature cells is essential for reducing the severity of the disease and reducing the number of people who require *** deep-learning(DL)model-based segmentation and categorization techniques have already been introduced,although they still have certain *** order to enhance feature extraction and classification in such a practical way,Mayfly optimization with Generative Adversarial Network(MayGAN)is introduced in this ***,Generative Adversarial System(GAS)is integrated with Principal Component Analysis(PCA)in the feature-extracted model to classify the type of blood cancer in the *** semantic technique and morphological procedures using geometric features are used to segment the cells that makeup *** lymphocytic Leukaemia(ALL),acute myelogenous Leukaemia(AML),chronic lymphocytic Leukaemia(CLL),chronic myelogenous Leukaemia(CML),and aberrant White Blood Cancers(WBCs)are all successfully classified by the proposed MayGAN *** proposed MayGAN identifies the abnormal activity in the WBC,considering the geometric *** with the state-of-the-art methods,the proposed MayGAN achieves 99.8%accuracy,98.5%precision,99.7%recall,97.4%F1-score,and 98.5%Dice similarity coefficient(DSC).

关键词： Leukemia blood smear images optimization classification neural networks

EsECC_SDN:Attack Detection and Classification Model for MANET

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Computers, Materials & Continua 2023年第3期74卷 6665-6688页

作者： Veera Ankalu Vuyyuru Youseef Alotaibi Neenavath veeraiah Saleh Alghamdi Korimilli Sirisha Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502A.PIndia Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharla521180A.PIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Electronics and Communications BVC Institute of Technology&ScienceAmalapuram533221A.PIndia

Mobile Ad Hoc Networks(MANET)is the framework for social networking with a realistic *** theMANETenvironment,based on the query,information is transmitted between the sender and *** the MANET network,the nodes within the communication range are involved in data *** the nodes that lie outside of the communication range are involved in the transmission of relay ***,due to the openness and frequent mobility of nodes,they are subjected to the vast range of security threats ***,it is necessary to develop an appropriate security mechanism for the dataMANET environment for data *** paper proposed a security framework for the MANET network signature escrow *** proposed framework uses the centralised Software Defined Network(SDN)with an ECC cryptographic *** developed security framework is stated as Escrow Elliptical Curve Cryptography SDN(EsECC_SDN)for attack detection and *** developed EsECC-SDN was adopted in two stages for attack classification and detection:(1)to perform secure data transmission between nodes SDN performs encryption and decryption of the data;and(2)to detect and classifies the attack in theMANET hyper alert based HiddenMarkovModel Transductive Deep ***,the EsECC_SDN is involved in the assignment of labels in the transmitted data in the database(DB).The escrow handles these processes,and attacks are evaluated using the hyper *** labels are assigned based on the k-medoids attack clustering through label assignment through a transductive deep learning *** proposed model uses the CICIDS dataset for attack detection and *** developed framework EsECC_SDN’s performance is compared to that of other classifiers such as AdaBoost,Regression,and Decision *** performance of the proposed EsECC_SDN exhibits∼3%improved performance compared with conventional techniques.

关键词： MANET security classifier cryptography attack escrow ECC

A New Method for Scene Classification from the Remote Sensing Images

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Computers, Materials & Continua 2022年第7期72卷 1339-1355页

作者： Purnachand Kollapudi Saleh Alghamdi Neenavath veeraiah Youseef Alotaibi Sushma Thotakura Abdulmajeed Alsufyani Department of CSE B V Raju Institute of TechnologyNarsapurMedakTelanganaIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaVijayawadaA.P.India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of ECE P.V.P Siddhartha Institute of TechnologyVijayawadaIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The mission of classifying remote sensing pictures based on their contents has a range of applications in a variety of *** recent years,a lot of interest has been generated in researching remote sensing image scene *** sensing image scene retrieval,and scene-driven remote sensing image object identification are included in the Remote sensing image scene understanding(RSISU)*** the last several years,the number of deep learning(DL)methods that have emerged has caused the creation of new approaches to remote sensing image classification to gain major breakthroughs,providing new research and development possibilities for RS image classification.A new network called Pass Over(POEP)is proposed that utilizes both feature learning and end-to-end learning to solve the problem of picture scene comprehension using remote sensing imagery(RSISU).This article presents a method that combines feature fusion and extraction methods with classification algorithms for remote sensing for scene *** benefits(POEP)include two *** multi-resolution feature mapping is done first,using the POEP connections,and combines the several resolution-specific feature maps generated by the CNN,resulting in critical advantages for addressing the variation in RSISU data ***,we are able to use Enhanced pooling tomake the most use of themulti-resolution feature maps that include second-order *** enablesCNNs to better cope with(RSISU)issues by providing more representative feature *** data for this paper is stored in a UCI dataset with 21 types of *** the beginning,the picture was pre-processed,then the features were retrieved using RESNET-50,Alexnet,and VGG-16 integration of *** characteristics have been amalgamated and sent to the attention layer,after this characteristic has been fused,the process of classifying the data will take *** utilize an ensemble classifier in our classification a

关键词： Remote sensing RSISU DL RESNET-50 VGG-16

Condition Monitoring of CNC Machining Using Adaptive Control

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International Journal of Automation and computing 2013年第3期10卷 202-209页

作者： B. Srinivasa Prasad D. Siva Prasad A. Sandeep G. veeraiah Department of Mechanical Engineering GITAM Institute of Technology Gandhi Institute of Technology and Management (GITAM) University

In this work, an adaptive control constraint system has been developed for computer numerical control （CNC） turning based on the feedback control and adaptive control/self-tuning control. In an adaptive controlled system, the signals from the online measurement have to be processed and fed back to the machine tool controller to adjust the cutting parameters so that the machining can be stopped once a certain threshold is crossed. The main focus of the present work is to develop a reliable adaptive control system, and the objective of the control system is to control the cutting parameters and maintain the displacement and tool flank wear under constraint valves for a particular workpiece and tool combination as per ISO standard. Using Matlab Simulink, the digital adaption of the cutting parameters for experiment has confirmed the efficiency of the adaptively controlled condition monitoring system, which is reflected in different machining processes at varying machining conditions. This work describes the state of the art of the adaptive control constraint （ACC） machining systems for turning. AIS14140 steel of 150 BHN hardness is used as the workpiece material, and carbide inserts are used as cutting tool material throughout the experiment. With the developed approach, it is possible to predict the tool condition pretty accurately, if the feed and surface roughness are measured at identical conditions. As part of the present research work, the relationship between displacement due to vibration, cutting force, flank wear, and surface roughness has been examined.

关键词： Adaptive control condition monitoring model based control system and flank wear surface roughness displacement.

Elastic and Optoelectronic Properties of KCdF3:ab initio Calculations through LDA/GGA/TB-mBJ within FP-LAPW Method

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Chinese Physics Letters 2015年第1期32卷 108-112页

作者： K. Ephraim Babu N. Murali K. Vijaya Babu B. Kishore Babu V. veeraiah Modelling and Simulation in Materials Science Laboratory Department of Physics Andhra University Visakhapatnam 530003 Andhra Pradesh India Department of Engineering Chemistry A UCE(A) Andhra University Visakhapatnam 530003 Andhra Pradesh India

Ab initio calculations are performed on the electronic, structural, elastic and optical properties of the cubic per- ovskite KCdF3. Tile Kohn Sham equations are solved by applying the full potential linearized augmented plane wave （FP-LAPW） method. The exchange correlation effects are included through the local density approximation （LDA ）, generalized gradient approximation （GGA） and modified Becke-Johnson （mBJ） exchange potential The calculated lattice constant is in good agreement with the experimental result. The elastic properties such as elastic constants, anisotropy factor, shear modulus, Young＇s modulus and Poisson＇s ratio are calculated. KCdF3 is ductile and elastically anisotropic. The calculations of the electronic band structure, density of states （DOS） and charge density show that this compound has an indirect energy band gap （M-F） with a mixed ionic and covalent bonding. The contribution of the different bands is analyzed from the total and partial density of states curves. Optical response of the dielectric functions, optical reflectivity, absorption coefficient, real part of optical conductivity, refractive index, extinction coefficient and electron energy loss, are presented for the energy range of O-40eV. The compound KCdF3 can be used for high-frequency optical and optoelectronic devices.

关键词： GGA Cd Elastic and Optoelectronic Properties of KCdF3:ab initio Calculations through LDA/GGA/TB-mBJ within FP-LAPW Method LDA FP

Vibrational and Electronic Spectra of 2-Phenyl-2-Imidazoline: A Combined Experimental and Theoretical Study

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Journal of Modern Physics 2018年第4期9卷 753-774页

作者： Yeddu Sushma Priya Kokkiripati Ramachandra Rao Pallavajhula Venkata Chalapathi Adamilli veeraiah Department of Physics Adikavi Nannaya University Rajamahendravaram India Crystal growth and Nano Science Research Centre Department of Physics Government College (A) Rajamahendravaram India Department of Physics University College of Engineering Javaharlal Nehru Technological University Guntur India Molecular Spectroscopy Laboratory Department of Physics DNR College (A) Bhimavaram India

The structural properties and vibrational frequencies of 2-phenyl-2-imidazoline have been investigated using theoretical and techniques by which a good correlation was observed. The assignments of the vibrational modes were performed with the help of normal co-ordinate analysis following the Scaled Quantum Mechanical Force Field methodology. Natural bond orbital analysis and the highest occupied molecular orbital-lowest unoccupied molecular orbital gap analysis have been carried out. UV-visible spectrum of the compound was recorded and compared with the theoretical UV-visible spectrum of the title molecule using Symmetry Adapted Cluster-Configuration Interaction method which yielded good agreement. Our results reflect that the title compound can be used as good source of UV light.

关键词： 2-Phenyl-2-Imidazoline DFT FT-IR FT-RAMAN NBO HOMO and LUMO