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Pattern Recognition of Modulation Signal Classification Using deep Neural Networks

Computer Systems Science & Engineering 2022年第11期43卷 545-558页

作者： d.venugopal V.Mohan S.Ramesh S.Janupriya Sangsoon Lim Seifedine Kadry department of Electronics and Communication Engineering KPR Institute of Engineering and TechnologyCoimbatore641048India department of Electronics and Communication Engineering Saranathan College of EngineeringTrichy620012India department of Computer Science and Engineering Krishnasamy College of Engineering&TechnologyCuddalore607109India department of Electronics and Communication Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India department of Computer Engineering Sungkyul UniversityAnyangKorea department of Applied data Science Noroff University CollegeKristiansandNorway

In recent times,pattern recognition of communication modulation signals has gained significant attention in several application areas such as military,civilian field,*** becomes essential to design a safe and robust feature extraction(FE)approach to efficiently identify the various signal modulation types in a complex *** works have derived new techniques to extract the feature parameters namely instant features,fractal features,and so *** addition,machine learning(ML)and deep learning(dL)approaches can be commonly employed for modulation signal *** this view,this paper designs pattern recognition of communication signal modulation using fractal features with deep neural networks(CSM-FFdNN).The goal of the CSM-FFdNN model is to classify the different types of digitally modulated *** proposed CSM-FFdNN model involves two major processes namely FE and *** proposed model uses Sevcik Fractal dimension(SFd)technique to extract the fractal features from the digital modulated ***,the extracted features are fed into the dNN model for modulation signal *** improve the classification performance of the dNN model,a barnacles mating optimizer(BMO)is used for the hyperparameter tuning of the dNN model in such a way that the dNN performance can be raised.A wide range of simulations takes place to highlight the enhanced performance of the CSM-FFdNN *** experimental outcomes pointed out the superior recognition rate of the CSM-FFdNN model over the recent state of art methods interms of different evaluation parameters.

关键词： Pattern recognition signal modulation communication signals deep learning feature extraction

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A Novel deep Neural Network for Intracranial Haemorrhage detection and Classification

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Computers, Materials & Continua 2021年第9期68卷 2877-2893页

作者： d.venugopal T.Jayasankar Mohamed Yacin Sikkandar Mohamed Ibrahim Waly Irina V.Pustokhina denis A.Pustokhin K.Shankar department of ECE KPR Institute of Engineering and TechnologyCoimbatore641407India department of Electronics and Communication Engineering University College of EngineeringBIT CampusAnna UniversityTiruchirappalli620024India department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia department of Logistics State University of ManagementMoscow109542Russia department of Computer Applications Alagappa UniversityKaraikudi630001India

data fusion is one of the challenging issues,the healthcare sector is facing in the recent *** diagnosis from digital imagery and treatment are deemed to be the right *** Haemorrhage(ICH),a condition characterized by injury of blood vessels in brain tissues,is one of the important reasons for *** generated by X-rays and Computed Tomography(CT)are widely used for estimating the size and location of *** use manual planimetry,a time-consuming process for segmenting CT scan *** Learning(dL)is the most preferred method to increase the efficiency of diagnosing *** this paper,the researcher presents a unique multi-modal data fusion-based feature extraction technique with deep Learning(dL)model,abbreviated as FFE-dL for Intracranial Haemorrhage detection and Classification,also known as *** proposed FFEdL-ICH model has four stages namely,preprocessing,image segmentation,feature extraction,and *** input image is first preprocessed using the Gaussian Filtering(GF)technique to remove ***,the density-based Fuzzy C-Means(dFCM)algorithm is used to segment the ***,the Fusion-based Feature Extraction model is implemented with handcrafted feature(Local Binary Patterns)and deep features(Residual Network-152)to extract useful ***,deep Neural Network(dNN)is implemented as a classification technique to differentiate multiple classes of *** researchers,in the current study,used benchmark Intracranial Haemorrhage dataset and simulated the FFEdL-ICH model to assess its diagnostic *** findings of the study revealed that the proposed FFEdL-ICH model has the ability to outperform existing models as there is a significant improvement in its *** future researches,the researcher recommends the performance improvement of FFEdL-ICH model using learning rate scheduling techniques for dNN.

关键词： Intracerebral hemorrhage fusion model feature extraction deep features classification

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deep Learning-Based Classification of Rotten Fruits and Identification of Shelf Life

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Computers, Materials & Continua 2024年第1期78卷 781-794页

作者： S.Sofana Reka Ankita Bagelikar Prakash venugopal V.Ravi Harimurugan devarajan Centre for Smart Grid Technologies School of Electronics EngineeringVellore Institute of TechnologyChennai600127India School of Electronics Engineering Vellore Institute of TechnologyChennai600127India department of Electrical Engineering Dr.B R Ambedkar National Institute of TechnologyJalandharPunjab144008India

The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality,flavor and nutritional *** primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to *** impact of rotten fruits can foster harmful bacteria,molds and other microorganisms that can cause food poisoning and other illnesses to the *** overall purpose of the study is to classify rotten fruits,which can affect the taste,texture,and appearance of other fresh fruits,thereby reducing their shelf *** agriculture and food industries are increasingly adopting computer vision technology to detect rotten fruits and forecast their shelf ***,this research work mainly focuses on the Convolutional Neural Network’s(CNN)deep learning model,which helps in the classification of rotten *** proposed methodology involves real-time analysis of a dataset of various types of fruits,including apples,bananas,oranges,papayas and ***,machine learningmodels such as GaussianNaïve Bayes(GNB)and random forest are used to predict the fruit’s shelf *** results obtained from the various pre-trained models for rotten fruit detection are analysed based on an accuracy score to determine the best *** comparison to other pre-trained models,the visual geometry group16(VGG16)obtained a higher accuracy score of 95%.Likewise,the random forest model delivers a better accuracy score of 88% when compared with GNB in forecasting the fruit’s shelf *** developing an accurate classification model,only fresh and safe fruits reach consumers,reducing the risks associated with contaminated ***,the proposed approach will have a significant impact on the food industry for efficient fruit distribution and also benefit customers to purchase fresh fruits.

关键词： Rotten fruit detection shelf life deep learning convolutional neural network machine learning gaussian naïve bayes random forest visual geometry group16

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Mechanism of microbial spore inactivation through electromagnetic radiations:a review

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Journal of Future Foods 2024年第4期4卷 324-334页

作者： Piyush Sharma Arun Prasath venugopal Parag Prakash Sutar Hong-wei Xiao Qi Zhang deparment of Food Process Engineering.National Institute of Techmology Rourkela Odisha 769008India College of Engineering China Agriculural UniversityBeijing 100083China School of Mechanical Engineering Yangzhou UTniversiny Yangzhou 225002China

Spores are the biological structures formed out of sporulation from vegetative cells in adverse *** tolerant to many extreme environment and conditions,they escape and survives critical processing steps in the food industry that poses food and health safety problems,as is evident from the increase in reports of food-bome outbreaks due to *** radiation(EM)is used for rapid decontamination and sterilization purposes in the food *** studies have reported a greater reduction in spore population upon irradiation with EM rays due to its impact on genomic material and other components of spores that destabilises overall structue and brings clonogenic death However,there is scattered literature regarding the mechanism of its inactivation and resistance against such *** review attempts to concisely evaluate the potential of electromagnetic radiations in spore inactivation and details its mechanism through a collective study of scientific results and *** also briefs about the process of sporulation,the structure of spores and the role of its components in the resistance of spores to *** studies,which demonstrated that combining various EM treatments might be an effective way for inactivation of spores,were discussed in detail.

关键词： Spore structure Electromagnetic radiations Mechanism of inactivation damage resistance

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Reversed-Phase-HPLC Assay Method for Simultaneous Estimation of Sorbitol, Sodium Lactate, and Sodium Chlorides in Pharmaceutical Formulations and drug Solution for Infusion

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American Journal of Analytical Chemistry 2024年第2期15卷 57-71页

作者： Sreenivas Pippalla venugopal Komreddy Srinivasulu Kasa Vaishnavi Chintala Poluri Venkata Reddy department of Chemistry Sikkim Professional University Gangtok India Analytical Research & development Hikma Pharmaceuticals USA Inc. Bedford USA department of Chemistry Osmania University Hyderabad India Analytical Research & development Cambrex High Point High Point USA department of Analytical Chemistry Annamalai University Annamalai Nagar India

A rapid, straightforward, sensitive, efficient, and cost-effective reverse-phase high-performance liquid chromatographic method was employed for the simultaneous determination of Sorbitol, Sodium Lactate, and Chlorides in a drug solution for infusion. Sorbitol, Sodium lactate, and Chloride are all officially recognized in the USP monograph. Assay methods are provided through various techniques, with titrations being ineffective for trace-level quantification. Alternatively, IC, AAS, and ICP-MS, though highly accurate, are costly and often unavailable to most testing facilities. When considering methods, it’s important to prioritize both quality control requirements and user-friendly techniques. A simple HPLC simultaneous method was developed for the quantification of Chlorides, Sorbitol, and Sodium Lactate with a shorter run time. The separation utilized a Shimpack SCR-102(H) ion exclusion analytical column (7.9 mm × 300 mm, 7 μm), with a flow rate of 0.6 mL per min. The column compartment temperature was maintained at 40°C, and the injection volume was set at 10 μL, with detection at 200 nm. All measurements were conducted in a 0.1% solution of phosphoric acid. The analytical curves demonstrated linearity (r > 0.9999) in the concentration range of 0.79 to 3.8 mg per mL for Sodium Lactate (SL), 0.16 to 0.79 mg per mL for Sodium Chloride (SC), and 1.5 to 7.2 mg per mL for Sorbitol. Validation of the developed method followed the guidelines of the International Conference on Harmonization (ICH Q2B) and USP. The method exhibited precision, robustness, accuracy, and selectivity. In accelerated stability testing over 6 months, no significant variations were observed in organoleptic analysis and pH. Consequently, the developed method is deemed suitable for routine quality control analyses, enabling the simultaneous determination of Sodium Lactate, Sodium Chloride, and Sorbitol in pharmaceutical formulations and infusions.

关键词： Sorbitol Sodium Lactate and Chloride Assay Analytical Validation HPLC

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Snapshot imaging of ultrashort electron bunches

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Light(Science & Applications) 2024年第7期13卷 1226-1228页

作者： Andreas döpp Ludwig-Maximilian-Universität München Am Coulombwall 185748GarchingGermany Max Planck Institut für Quantenoptik Hans-Kopfermann-Strasse 1Garching85748Germany

New measurements combine spatial and temporal information from optical transition radiation to estimate the three-dimensional structure of electron bunches from a laser wakefield accelerator.

关键词： ultrashort Snapshot electron

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Influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel

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Applied Mathematics and Mechanics(English Edition) 2024年第3期45卷 563-580页

作者： N.HUMNEKAR d.SRINIVASACHARYA department of Mathematics National Institute of TechnologyWarangal 506004TelanganaIndia

The influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel is *** darcyBrinkman model is used to characterize the fluid flow dynamics in porous *** analytical solutions are obtained for the unidirectional and completely developed *** on a normal mode analysis,the generalized eigenvalue problem under a perturbed state is *** eigenvalue problem is then solved by the spectral ***,the critical Rayleigh number with the corresponding wavenumber is evaluated at the assigned values of the other flow-governing *** results show that increasing the darcy number,the Lewis number,the dufour parameter,or the Soret parameter increases the stability of the system,whereas increasing the inclination angle of the channel destabilizes the ***,the flow is the most unstable when the channel is vertically oriented.

关键词： nanofluid inclined channel variable viscosity linear stability double dif-fusion porous medium

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decomposition mechanisms of nuclear-grade cationic exchange resin by advanced oxidation processes:Statistical molecular fragmentation model and dFT calculations

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Journal of Environmental Sciences 2024年第1期135卷 433-448页

作者： Xiang Meng Pierre désesquelles Lejin Xu department of Nuclear Engineering and Technology School of Energy and Power EngineeringHuazhong University of Science&TechnologyWuhan 430074China CNRS Laboratoire de Physique des Gaz et des PlasmasUniversitéParis-SaclayOrsay 91405France State Key Laboratory of Coal Combustion School of Energy and Power EngineeringHuazhong University of Science and TechnologyWuhan 430074China

The treatment and disposal of radioactive waste are presently facing great *** ion exchange resins have become a focus of attention due to their high production and serious environmental *** this paper,a simplified model of cationic exchange resin is proposed,and the degradation processes of cationic resin monomer initiated by hydroxyl radicals(·OH)are clarified by combining statistical molecular fragmentation(SMF)model and density functional theory(dFT)*** prediction of active sites indicates that the S-O bonds and the C-S bond of the sulfonic group are more likely to react during the *** meta-position of the sulfonic group on the benzene ring is the most active site,and the benzene ring without the sulfonic group has a certain *** C11-C14 and C17-C20 bonds,on the carbon skeleton,are the most easily *** is also found that dihydroxy addition and elimination reactions play a major role in the process of desulfonation,carbon skeleton cleavage and benzene ring *** decomposition mechanisms found through the combination of physical models and chemical calculations,provide theoretical guidance for the treatment of complex polycyclic aromatic hydrocarbons.

关键词： Cationic exchange resin Statistical molecular fragmentation model density functional theory Hydroxyl radical decomposition mechanism

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Role of pituitary adenylate cyclase-activating polypeptide in peripheral nerve regeneration:a cellular and molecular perspective

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Neural Regeneration Research 2024年第7期19卷 1429-1430页

作者： Grazia Maugeri Velia d’Agata Section of Anatomy Histology and Movement SciencesDepartment of Biomedical and Biotechnological SciencesUniversity of CataniaCataniaItaly

Neuro regeneration is a very complex phenomenon characterized by the generation of new neurons and synapses,involving connections between adjacent cells and axonal *** supplies additional longterm resources to replace... 详细信息

关键词： replace functional regeneration

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Process engineering of demineralisation of moderate to high ash Indian coals through NaOH‑HCl leaching and HF leaching

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International Journal of Coal Science & Technology 2024年第2期11卷 111-122页

作者： Heena dhawan d.K.Sharma ANRF Ministry of ScienceNew DelhiIndia department of Energy Science and Engineering Indian Institute of Technology DelhiNew Delhi 110016India

Chemical leaching of coals would be required to produce cleaner coals for some special applications where physical benefi-ciation may not be effective *** would also help in recovering Li and rare earth metals besides in the sequestration of CO_(2).About 20 Indian coals having complexly distributed moderate to high ash contents were sequentially treated with various alkali–acid such as NaOH-HCl,HF,HCl,HCl-HF,and NaOH-HCl-HF *** aimed to establish and design the best stepwise sequential process for the highest degree of demineralisation through a chemical leaching *** and process intensification studies were carried *** than 80%demineralisation of Madhaipur and Neemcha coals was observed using the best sequential treatment designed *** repeated stepwise treatment of the alkali and the acid was also studied,which was found to significantly enhance the degree of demineralisation of *** integrated process of alkali–acid leaching followed by solvent extraction(Organo-refining)and vice versa of the treated coal was also studied for producing cleaner coals.

关键词： Alkali–acid leaching demineralisation Integrated process Rare earth elements

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