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MIoT Based Skin Cancer Detection Using Bregman Recurrent Deep Learning

Computers, Materials & Continua 2022年第12期73卷 6253-6267页

作者： Nithya Rekha sivakumar Sara Abdelwahab Ghorashi Faten Khalid Karim Eatedal Alabdulkreem Amal Al-Rasheed Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Mobile clouds are the most common medium for aggregating,storing,and analyzing data from the medical Internet of Things(MIoT).It is employed to monitor a patient’s essential health signs for earlier disease diagnosis and *** the various disease,skin cancer was the wide variety of cancer,as well as enhances the endurance *** recent years,many skin cancer classification systems using machine and deep learning models have been developed for classifying skin tumors,including malignant melanoma(MM)and other skin ***,accurate cancer detection was not performed with minimum time *** order to address these existing problems,a novel Multidimensional Bregman Divergencive Feature Scaling Based Cophenetic Piecewise Regression Recurrent Deep Learning Classification(MBDFS-CPRRDLC)technique is introduced for detecting cancer at an earlier *** MBDFS-CPRRDLC performs skin cancer detection using different layers such as input,hidden,and output for feature selection and *** patient information is composed of *** patient information was stored in mobile clouds server for performing predictive *** collected data are sent to the recurrent deep learning *** the first hidden layer,the feature selection process is carried out using the Multidimensional Bregman Divergencive Feature Scaling technique to find the significant features for disease identification resulting in decreases time *** by,the disease classification is carried out in the second hidden layer using cophenetic correlative piecewise regression for analyzing the testing and training *** process is repeatedly performed until the error gets *** this way,disease classification is accurately performed with higher *** evaluation is carried out for factors namely Accuracy,precision,recall,F-measure,as well as cancer detection time,by the amount of patient *** observed result confirms that the pr

关键词： MIoT skin cancer detection recurrent deep learning classification multidimensional bregman divergencive scaling cophenetic correlative piecewise regression

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Can the Grain-for-Green Program Really Ensure a Low Sediment Load on the Chinese Loess Plateau?

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Engineering 2019年第5期5卷 855-864页

作者： Pengcheng Sun Yiping Wu Zhifeng Yang Bellie sivakumar Linjing Qiu Shuguang Liu Yanpeng Cai Department of Earth and Environmental Science School of Human Settlements and Civil EngineeringXi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of Water Environment Simulation School of EnvironmentBeijing Normal UniversityBeijing 100875China School of Civil and Environmental Engineering The University of New South WalesSydneyNSW 2052Australia Department of Land Air and Water ResourcesUniversity of CaliforniaDavisCA 95616USA Department of Civil Engineering Indian Institute of Technology BombayMumbai 400076India National Engineering Laboratory for Applied Technology of Forestry and Ecology in South China Central South University of Forestry and TechnologyChangsha 410004China

The Chinese Loess Plateau is the most seriously eroded area in the world and contributes the vast majority of the sediment that goes into the Yellow *** the 1950s,progressive soil and water conservation measures have been implemented—in particular,large-scale ecological restoration has been ongoing since 1999—resulting in a significant reduction of the sediment ***,the mechanism of the sediment transport dynamics is not fully understood due to multiple and complicated influencing factors including climate change and human activities(e.g.,ecological restoration).A challenging question,then,arises:Is the current low sediment level a“new normal”in this era and in the future?To address this question,we selected a typical loess hilly region where considerable ecological restoration has been implemented,and which is regarded as the site of the first and most representative Grainfor-Green program in the Loess *** investigated the evolution of discharge–sediment relationships in the past decades(1960–2010)and their association with the soil and water conservation measures in this *** results showed that there was a distinct change in the regression parameters of the commonly used annual discharge–sediment regression equation—a continuously increasing trend of parameter b and a decreasing trend of parameter a,accompanying the ecological *** increase in exponent b(i.e.,a steeper slope)implies a potential lower sediment load resulting from low discharge and a potential higher sediment load resulting from large *** finding may question the new normal of a low sediment level and implies the potential risk of a large sediment load during extremely wet years.

关键词： Discharge–sediment relationship Ecological restoration Loess hilly region Sediment load Sediment rating parameters

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EfficientNetV2 Model for Plant Disease Classification and Pest Recognition

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Computer Systems Science & Engineering 2023年第5期45卷 2249-2263页

作者： R.S.Sandhya Devi V.RVijay Kumar P.sivakumar Department of EEE Kumaraguru College of TechnologyCoimbatore641049India Department of Electronics and Communication Engineering Anna University Regional CampusCoimbatore641046India Department of EEE PSG College of TechnologyCoimbatore641004India

Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of *** perform the investigation on Plant and pest classification,Transfer Learning(TL)approach is used on *** requires limited labelled data and shorter training ***,the limitation of TL is the pre-trained model network’s topology is static and the knowledge acquired is detrimentally overwriting the old ***-V2 is a Convolutional Neural Network(CNN)model with significant high speed learning rates across variable sized *** model employs a form of progressive learning mechanism which expands the network topology gradually over the course of training process improving the model’s learning *** provides a better interpretability of the model’s understanding on the test *** these insights,our work investigates the effectiveness of EfficienetV2 model trained on a class imbalanced dataset for plant disease classification and pest recognition by means of combining TL and progressive learning *** Progressive Learning for TL(PL-TL)is used in our work consisting of 38 classes of PlantVillage dataset of crops and fruit species,5 classes of cassava leaf diseases and another dataset with around 102 classes of crop pest images downloaded from popular dataset platforms,though it is not a benchmark *** test the predictability rate of the model in classifying leaf diseases with similar visual symptoms,Mix-up data augmentation technique is used at the ratio of 1:4 on corn and tomato classes which has high probability of misinterpretation of disease ***,the paper compares the TL approach performed on the above mentioned three types of data set using well established CNN based Inceptionv3,and Vision Transformer a non-CNN *** clearly depicts that EfficientNetV2 has an out

关键词： Image classification transfer learning efficientNetV2 mix-up data augmentation inception V3

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Statistical optimization and anticancer activity of a red pigment isolated from Streptomyces sp. PM4

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Asian Pacific Journal of Tropical Biomedicine 2013年第8期3卷 650-656页

作者： Valliappan Karuppiah Chandramohan Aarthi Kannan sivakumar Lakshmanan Kannan CAS in Marine Biology Faculty of Marine SciencesAnnamalai UniversityParangipettai 608502Tamil NaduIndia Marine Biotechnology Laboratory State Key Laboratory of Microbial Metabolism and School of Life Sciences and BiotechnologyShanghai Jiao TongUniversityShanghai 200240P.R. China

Objective:To enhance the pigment production ***4 for evaluating its anticancer ***:Response surface methodology was employed to enhance the production of red pigment *** pigment was purified and evaluated for the anticancer activity against HT1080,Hep2,HeLa and MCF7 cell lines by MTT ***:Based on the response surface methodology,it could be concluded that maltose (4.06 g),peptone (7.34 g),yeast extract(4.34 g)and tyrosine(2.89 g)were required for the maximum production of pigment(1.68 g/L)by *** of the medium with the above tested features increased the pigment yield by 4.6 *** showed the potential anticancer activity against HT1080,HEp-2,HeLa and MCF-7cell lines with the IC50value of 18.5,15.3,9.6 and 8.5 ***:The study revealed that the maximum amount of pigment could be produced to treat cancer.

关键词： Streptomyces Pigment Response surface methodology Anticancer activity

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Experimental investigation and ANN modeling on improved performance of an innovative method of using heave response of a non-floating object for ocean wave energy conversion

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Frontiers in Energy 2013年第3期7卷 279-287页

作者： Srinivasan CHANDRASEKARAN Arunachalam AMARKARTHIK Karuppan sivakumar Dhanasekaran SELVAMUTHUKUMARAN Shaji SIDNEY Department of Ocean Engineering Indian Institute of TechnologyMadras Chennai 600036 India Department of Mechanical Engineering Bannari Amman Institute ofTechnology TamilNadu 638401 India

To convert wave energy into usable forms of energy by utilizing heaving body, heaving bodies （buoys） which are buoyant in nature and float on the water surface are usually used. The wave exerts excess buoyancy force on the buoy, lifting it during the approach of wave crest while the gravity pulls it down during the wave trough. A hydraulic, direct or mechanical power takeoff is used to convert this up and down motion of the buoy to produce usable forms of energy. Though using a floating buoy for harnessing wave energy is conventional, this device faces many challenges in improving the overall conversion efficiency and survivability in extreme conditions. Up to the present, no studies have been done to harness ocean waves using a non-floating object and to find out the merits and demerits of the system. In the present paper, an innovative heaving body type of wave energy converter with a non-floating object was proposed to harness waves. It was also shown that the conversion efficiency and safety of the proposed device were significantly higher than any other device proposed with floating buoy. To demonstrate the improvements, experiments were conducted with non- floating body for different dimensions and the heave response was noted. Power generation was not considered in the experiment to observe the worst case response of the heaving body. The device was modeled in artificial neural network （ANN）, the heave response for various parameters were predicted, and compared with the experimental results. It was found that the ANN model could predict the heave response with an accuracy of 99%.

关键词： ocean wave energy point absorbers heaving body non-floating object heave response ratio artificial neural network (ANN)

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Synthesis of biodegradable Mg-Zn alloy by mechanical alloying: Statistical prediction of elastic modulus and mass loss using fractional factorial design

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Transactions of Nonferrous Metals Society of China 2018年第4期28卷 687-699页

作者： Emee Marina SALLEH Zuhailawati HUSSAIN sivakumar RAMAKRISHNAN Biomaterials Niche Area School of Materials and Mineral Resources EngineeringEngineering CampusUniversiti Sains Malaysia14300 Nibong TebalPenangMalaysia School of Applied Physics Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangorMalaysia

Biodegradable Mg-Zn alloy was synthesized using mechanical alloying where a statistical model was developed using fractional factorial design to predict elastic modulus and mass loss of the bulk *** effects of mechanical alloying parameters(i.e.,milling time,milling speed,ball-to-powder mass ratio and Zn content)and their interactions were investigated involving 4 numerical factors with 2 replicates,thus 16 runs of two-level fractional factorial *** of analysis of variance(ANOVA),regression analysis and R2 test indicated good accuracy of the *** statistical model determined that the elastic modulus of biodegradable Mg-Zn alloy was between 40.18 and 47.88 GPa,which was improved and resembled that of natural bone(30-57 GPa).Corrosion resistance(mass loss of pure Mg,33.74 mg)was enhanced with addition of 3%-10%Zn(between 9.32 and 15.38 mg).The most significant independent variable was Zn content,and only the interaction of milling time and ball-to-powder mass ratio was significant as P-value was less than ***,mechanical properties(represented by elastic modulus)and corrosion resistance(represented by mass loss)of biodegradable Mg-Zn alloy can be statistically predicted according to the developed models.

关键词： biodegradable Mg-Zn alloy mechanical alloying fractional factorial design elastic modulus mass loss

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Biopeptides of Pyropia yezoensis and their potential health benefits: A review

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Asian Pacific Journal of Tropical Biomedicine 2021年第9期11卷 375-384页

作者： sivakumar Allur Subramaniyan Naziya Begum Sung Jae Kim Youn Hee Choi Taek-Jeong Nam Institute of Fisheries Sciences Pukyong National UniversityBusan 46041South Korea Department of Chemistry College of Natural and computational sciencesDebre Berhan UniversityDebye BerhanP.O.Box-445 Ethiopia Department of Orthopaedic Surgery Dongtan Sacred Heart HospitalHallym University College of MedicineHwaseongRepublic of Korea Department of Marine Bio-Materials&Aquaculture Pukyong National UniversityBusan 48513South Korea

Pyropia yezoensis(***)is a popular species of red algae that are commercially cultivated and consumed in East Asia,China,Japan,and *** high protein content of *** provides a source of multiple bioactive peptides exhibiting antioxidant,anti-inflammatory,antihypertensive,anticancer,tissue healing,immunomodulatory,and anticoagulant ***,many other biologically active substances in ***,including carbohydrates,lipids,dietary fibers,and polyphenols,have shown potential health benefits and are important in both the food and agriculture *** review provides a detailed summary of researches over the last decade on the biological and medicinal properties of bioactive *** information was extracted from various electronic resources,including Google Scholar,PubMed,MEDLINE,and Google Patents.

关键词： Red algae Pyropia Bioactive peptides Human health

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Isolation of protein from Chlorella sorokiniana CY1 using liquid biphasic flotation assisted with sonication through sugaring-out effect

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Journal of Oceanology and Limnology 2019年第3期37卷 898-908页

作者： CHIA Shir Reen CHEW Kit Wayne SHOW Pau Loke sivakumar Manickam LING Tau Chuan TAO Yang Bioseparation Research Group Department of Chemical and Environmental EngineeringFaculty of EngineeringUniversity of Nottingham Malaysia CampusSemenyih 43500Malaysia Department of Chemical and Environmental Engineering Faculty of EngineeringUniversity of Nottingham Malaysia CampusSemenyih 43500Malaysia Institute of Biological Sciences Faculty of ScienceUniversity of MalayaKuala Lumpur 50603Malaysia College of Food Science and Technology Nanjing Agricultural UniversityNanjing 210095China

Microalgae,a sustainable source of multi beneficial components has been discovered and could be utilised in pharmaceutical,bioenergy and food *** study aims to investigate the sugaring-out effect on the recovery of protein from wet green microalga,Chlorella sorokiniana CY1 which was assisted with sonication.A comparison of monosaccharides and disaccharides as one of the phaseforming constituents shows that the monosaccharides,glucose was the most suitable sugar in forming the phases with acetonitrile to enhance the production of protein(52% of protein).The protein productivity of microalgae was found to be significantly influenced by the volume ratio of both phases,as the yield of protein increased to 77%.The interval time between the sonication as well as the sonication modes were influencing the protein productivity as *** optimum protein productivity was obtained with 10s of resting time in between *** mode of sonication was suitable to break down the cell wall of microalgae compared to continuous mode as a lower protein yield was obtained with the application of continuous *** optimum condition for protein extraction were found as followed:200g/L glucose as bottom phase with volume ratio of 1:1.25,10s of resting time for ultrasonication,5s of ultrasonication in pulse mode and 0.25g of biomass *** high yield of protein about 81% could be obtained from microalgae which demonstrates the potential of this source and expected to play an important role in the future.

关键词： sugaring-out Chlorella sorokiniana CY1 liquid biphasic flotation sonication microalgae extraction

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2D spinel ZnCo_(2)O_(4) microsheet-coated functional separator for promoted redox kinetics and inhibited polysulfide dissolution

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Journal of Energy Chemistry 2021年第4期30卷 468-475页

作者： Jeong Seok Yeon Tae Ho Park Young Hun Ko Periyasamy sivakumar Jun Su Kim Youngkywon Kim Ho Seok Park School of Chemical Engineering Sungkyunkwan UniversitySuwon 16419Gyeonggi-doRepublic of Korea Advanced Batteries Research Center Korea Electronics Technology InstituteSeongnam 13509Gyeonggi-doRepublic of Korea Department of Health Sciences and Technology Samsung Advanced Institute for Health Sciences and Technology(SAIHST)Sungkyunkwan UniversitySuwon 16419Gyeonggi-doRepublic of Korea Department of Chemistry Dongguk University-Seoul CampusJung-gu 04620 SeoulRepublic of Korea

Lithium-sulfur(Li-S)batteries are receiving increasing attention as one of the potential next-generation batteries,owing to their high energy densities and low ***,practical Li-S batteries with high energy densities are extremely hindered by the sulfur loss,low Coulombic efficiency,and short cycling life originating from the polysulfide(LiPS)*** this study,two-dimensional(2D)ZnCo_(2)O_(4) microsheets fabricated by a facile hydrothermal process are employed to modify the separator,for improving the electrochemical performances of Li-S *** resulting 2D Zn Co_(2)O_(4)-coated separator features a coating thickness of approximately 10 lm,high ionic conductivity of 1.8 m S/cm,and low mass loading of 0.2 mg/cm^(2).This 2D ZnCo_(2)O_(4)-coated separator effectively inhibits Li PS shuttle by a strong chemical interaction with Li PS as well as promotes the redox kinetics by Zn CO2O4-coated layers,as determined by X-ray photoelectron spectroscopy analysis,self-discharge,time-dependent permeation test,Li symmetric cell test,and Li2S nucleation ***,the Li-S batteries based on the 2D Zn Co_(2)O_(4)-coated separator exhibit a high initial discharge capacity of 1292.2 m Ah/g at 0.1 ***,they exhibit excellent long cycle stability at 1 and 2 C with capacity retention of 84%and 86%even after800 cycles,corresponding to a capacity fading rate of 0.020%and 0.016%per cycle,***,these Li-S cells with a high sulfur loading at 5.3 mg/cm^(2) and low electrolyte concentration of 9 l L/mg deliver a high discharge capacity of 4.99 m Ah/cm^(2) after 200 cycles at 0.1 C.

关键词： Lithium sulfur batteries Functional separator 2D microsheet Polysulfide Redox kinetics

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An Efficient 3D CNN Framework with Attention Mechanisms for Alzheimer’s Disease Classification

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Computer Systems Science & Engineering 2023年第11期47卷 2097-2118页

作者： Athena George Bejoy Abraham Neetha George Linu Shine sivakumar Ramachandran Department of Electronics and Communication Engineering College of EngineeringTrivandrum695016India Department of Computer Science and Engineering College of Engineering MuttatharaTrivandrum695008India Department of Electronics and Communication Rajeev Gandhi Institute of TechnologyKottayam686501India Department of Electronics and Communication Engineering Government Engineering CollegeWayanad670644India

Neurodegeneration is the gradual deterioration and eventual death of brain cells,leading to progressive loss of structure and function of neurons in the brain and nervous *** disorders,such as Alzheimer’s,Huntington’s,Parkinson’s,amyotrophic lateral sclerosis,multiple system atrophy,and multiple sclerosis,are characterized by progressive deterioration of brain function,resulting in symptoms such as memory impairment,movement difficulties,and cognitive *** diagnosis of these conditions is crucial to slowing down cell degeneration and reducing the severity of the *** resonance imaging(MRI)is widely used by neurologists for diagnosing brain *** majority of the research in this field focuses on processing the 2D images extracted from the 3D MRI volumetric scans for disease *** might result in losing the volumetric information obtained from the whole brain *** address this problem,a novel 3D-CNN architecture with an attention mechanism is proposed to classify whole-brain MRI images for Alzheimer’s disease(AD)*** 3D-CNN model uses channel and spatial attention mechanisms to extract relevant features and improve accuracy in identifying brain dysfunctions by focusing on specific regions of the *** pipeline takes pre-processed MRI volumetric scans as input,and the 3D-CNN model leverages both channel and spatial attention mechanisms to extract precise feature representations of the input MRI volume for accurate *** present study utilizes the publicly available Alzheimer’s disease Neuroimaging Initiative(ADNI)dataset,which has three image classes:Mild Cognitive Impairment(MCI),Cognitive Normal(CN),and AD *** proposed approach achieves an overall accuracy of 79%when classifying three classes and an average accuracy of 87%when identifying AD and the other two *** findings reveal that 3D-CNN models with an attention mechanism exhibit significantly higher classi

关键词： 3D CNN alzheimer’s disease attention mechanism classification

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