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Web-based remote sensing image retrieval using multiscale and multidirectional analysis based on Contourlet and Haralick texture features

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International Journal of Intelligent Computing and Cybernetics 2021年第4期14卷 533-549页

作者： Rajakumar Krishnan arunkumar thangavelu P.Prabhavathy Devulapalli Sudheer Deepak Putrevu Arundhati Misra School of Computer Science and Engineering Vellore Institute of TechnologyVelloreIndia School of Information Technology and Engineering Vellore Institute of TechnologyVelloreIndia School of Computer Science and Engineering Vellore Institute of TechnologyVelloreIndiaand Space Applications Centre AhmedabadIndia

Purpose-Extracting suitable features to represent an image based on its content is a very tedious *** in remote sensing we have high-resolution images with a variety of objects on the Earth’s *** distance metric is used to measure the similarity between query and database *** low distance obtained image is indexed at the top as high relevant information to the ***/methodology/approach-This paper aims to develop an automatic feature extraction system for remote sensing image *** texture features based on Contourlet transform are fused with statistical features extracted from the QuadTree(QT)decomposition are developed as feature set to represent the input *** extracted features will retrieve similar images from the large image datasets using an image-based query through the web-based user ***-The developed retrieval system performance has been analyzed using precision and recall and F1 *** proposed feature vector gives better performance with 0.69 precision for the top 50 relevant retrieved results over other existing multiscale-based feature extraction ***/value-The main contribution of this paper is developing a texture feature vector in a multiscale domain by combining the Haralick texture properties in the Contourlet domain and Statistical features using QT *** features required to represent the image is 207 which is very less dimension compare to other texture *** performance shows superior than the other state of art methods.

关键词： Image retrieval Remote sensing Contourlet Texture features Web-based search CBIR Multiscale texture

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More on the interplay between gut microbiota,autophagy,and inflammatory bowel disease is needed

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World Journal of Gastroenterology 2024年第27期30卷 3356-3360页

作者： arunkumar Subramanian Afrarahamed Jahabardeen Tamilanban Thamaraikani Chitra Vellapandian Department of Pharmacology SRM College of PharmacySRM Institute of Science and TechnologyKattankulathurChennai 603203India

The concept of inflammatory bowel disease(IBD),which encompasses Crohn’s disease and ulcerative colitis,represents a complex and growing global health concern resulting from a multifactorial *** dysfunctional autophagy and dysbiosis contribute to IBD,with their combined effects exacerbating the related inflammatory *** a result,the existing interconnection between gut microbiota,autophagy,and the host’s immune system is a decisive factor in the occurrence of *** factors that influence the gut microbiota and their impact are another important point in this *** on this initial perspective,this manuscript briefly highlighted the intricate interplay between the gut microbiota,autophagy,and IBD *** addition,it also addressed the potential targeting of the microbiota and modulating autophagic pathways for IBD therapy and proposed suggestions for future research within a more specific and expanded *** studies are warranted to explore restoring microbial balance and regulating autophagy mechanisms,which may offer new therapeutic avenues for IBD management and to delve into personalized treatment to alleviate the related burden.

关键词： Inflammatory bowel disease Gut microbiota Autophagy Crohn’s disease Ulcerative colitis

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Autism Spectrum Disorder Diagnosis Using Ensemble ML and Max Voting Techniques

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Computer Systems Science & Engineering 2022年第4期41卷 389-404页

作者： A.arunkumar D.Surendran Computer science and Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Computer Science and Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India

Difﬁculty in communicating and interacting with other people are mainly due to the neurological disorder called autism spectrum disorder(ASD)*** diseases can affect the nerves at any stage of the human being in childhood,adolescence,and *** is known as a behavioral disease due to the appearances of symptoms over theﬁrst two years that continue until *** of the studies prove that the early detection of ASD helps improve the behavioral characteristics of patients with *** detection of ASD is a very challenging task among various *** learning(ML)algorithms still act very intelligent by learning the complex data and pre-dicting quality *** this paper,ensemble ML techniques for the early detec-tion of ASD are *** this detection,the dataset isﬁrst processed using three ML algorithms such as sequential minimal optimization with support vector machine,Kohonen self-organizing neural network,and random forest *** prediction results of these ML algorithms(ensemble)further use the bagging concept called max voting to predict theﬁnal *** accuracy,sensitivity,and speciﬁcity of the proposed system are calculated using confusion *** pro-posed ensemble technique performs better than state-of-the art ML algorithms.

关键词： SVM autism disorder Kohonen SONN max voting ensemble machine learning technique random forest SMO–SVM bootstrap gradient boosting

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Secure and Light Weight Elliptic Curve Cipher Suites in SSL/TLS

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Computer Systems Science & Engineering 2022年第1期40卷 179-190页

作者： B.arunkumar G.Kousalya Coimbatore Institute of Technology Coimbatore641014India

In the current circumstance,e-commerce through an online banking system plays a significant *** may either buy goods from E-Commerce websites or use online banking to move money to other *** a user participates in these types of behaviors,their sensitive information is sent to an untrust-worthy *** a consequence,when transmitting data from an internal browser to an external E-commerce web server using the cryptographic protocol SSL/TLS,the E-commerce web server ensures the security of the user’s *** user should be pleased with the confidentiality,authentication,and authenticity properties of the SSL/TLS on both the user’s web browser and the remote E-commerce web server.E-Commerce web servers should choose the best SSL/TLS cipher suites for negotiating the user in order to attain such optimistic scenarios,as the cipher suite used in SSL/TLS plays an important role in securing E-Commerce web *** paper primarily focuses on analyzing the SSL/TLS cipher and elliptic *** paper also recommends the best elliptic curve cipher suites for E-Commerce and online banking servers,based on their power consumption,handshake execution time,and key exchange and signature verification time.

关键词： Elliptic curve cipher suites secp256r1 curve25519 ed25519

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Robust multifocus deep neural network for progression prediction on patient trajectory data

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International Journal of Intelligent Computing and Cybernetics 2022年第4期15卷 589-598页

作者： K.arunkumar S.Vasundra Department of CSE JNTUAAnanthapuramIndia Department of CSE JNTUACEAAnanthapuramIndia

Purpose-Patient treatment trajectory data are used to predict the outcome of the treatment to particular disease that has been carried out in the *** order to determine the evolving disease on the patient and changes in the health due to treatment has not considered existing *** deep learning models to trajectory data mining can be employed to identify disease prediction with high accuracy and less computation ***/methodology/approach-Multifocus deep neural network classifiers has been utilized to detect the novel disease class and comorbidity class to the changes in the genome pattern of the patient trajectory data can be identified on the layers of the *** is employed to learn extracted feature set with activation and weight function and then merged on many aspects to classify the undetermined sequence of diseases as a new *** performance of disease progression learning progress utilizes the precision of the constituent classifiers,which usually has larger generalization benefits than those optimized ***-Deep learning architecture uses weight function,bias function on input layers and max *** of the input layer has applied to hidden layer to generate the multifocus characteristics of the disease,and multifocus characterized disease is processed in activation function using ReLu function along hyper parameter tuning which produces the effective outcome in the output layer of a fully connected *** results have proved using cross validation that proposed model outperforms methodologies in terms of computation time and ***/value-Proposed evolving classifier represented as a robust architecture on using objective function to map the data sequence into a class distribution of the evolving disease class to the patient ***,the generative output layer of the proposed model produces the progression outcome of the disease of the particular pa

关键词： Patient trajectory data Deep learning representatives Disease evolution Unstructured hierarchical data Cluster reconstruction error

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Optimum Design of Stair-Climbing Robots Using Taguchi Method

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Intelligent Automation & Soft Computing 2023年第1期35卷 1229-1244页

作者： A.arunkumar S.Ramabalan D.Elayaraja Department of Mechanical Engineering E.G.S.Pillay Engineering CollegeNagapattinamTamilnaduIndia Department of Mechanical Engineering QIS College of Engineering and TechnologyOngoleAndhra PradeshIndia

Environmental issues like pollution are major threats to human *** systems are developed to reduce *** this paper,an optimal mobile robot design to reduce pollution in Green supply chain management *** supply chain management involves as similating environmentally and eco-nomically feasible solutions into the supply chain ***,advanced technologies,and advanced networks are becoming pillars of a sustainable supply chain management *** the same time,there is much change happening in the logistics *** are moving towards a new logistics *** the new model,robotic logistics has a vital *** reasons for this change are the rapid growth of the e-commerce business and the shortage of *** advantages of using robotic logistics are reduction in human errors,faster delivery speed,better customer satisfaction,more safety for workers,and high workforce adaptability.A robot with rocker-bogie suspension is a six-wheeled mobile platform that has a distinctive potential to keep all wheels on the ground *** has been designed to traverse rough and uneven terrain by distributing the load over its wheels ***,there is a limitation to achieving high-speed mobility against vertical *** this research,an optimal design of product delivery wheeled robots for a sustainable supply chain system is proposed to ensure higher adaptability and maximum stability during climbing *** design parameters of the proposed robot are optimized using Taguchi *** aim is to get a smooth trajectory of the robot’s *** proposed approach realizes a robot with much-improved stability which can climb over heights more than the size of the wheel(i.e.,3 times the radius of wheels).The results reveal that the modified rocker-bogie system not only increases the stair-climbing capability but also thwarts instability due to overturning of a wheel of the robot.

关键词： Green supply chain management robotic logistics stair-climbing wheeled mobile robot optimum design rocker-bogie mechanism taguchi method

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Healthcare Monitoring Using Ensemble Classifiers in Fog Computing Framework

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Computer Systems Science & Engineering 2023年第5期45卷 2265-2280页

作者： P.M.arunkumar Mehedi Masud Sultan Aljahdali Mohamed Abouhawwash Department of Computer Science and Engineering Karpagam College of EngineeringCoimbatore641032India Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Nowadays,the cloud environment faces numerous issues like synchronizing information before the switch over the data *** requirement for a centralized internet of things(IoT)-based system has been restricted to some *** to low scalability on security considerations,the cloud seems *** healthcare networks demand computer operations on large amounts of data,the sensitivity of device latency evolved among health networks is a challenging *** comparison to cloud domains,the new paradigms of fog computing give fresh alternatives by bringing resources closer to users by providing low latency and energy-efficient data processing *** fog computing frameworks have various flaws,such as overvaluing response time or ignoring the accuracy of the result yet handling both at the same time compromises the network *** this proposed work,Health Fog is integrated with the Optimized Cascaded Convolution Neural Network framework for diagnosing heart ***,the data is collected,and then pre-processing is done by Linear Discriminant *** the features are extracted and optimized using Galactic Swarm *** optimized features are given into the Health Fog framework for diagnosing heart disease *** uses ensemble-based deep learning in edge computing devices,which automatically monitors real-life health networks such as heart disease ***,the classifiers such as bagging,boosting,XGBoost,Multi-Layer Perceptron(MLP),and Partitions(PART)are used for classifying the *** the majority voting classifier predicts the *** work uses FogBus architecture and evaluates the execution of power usage,bandwidth of the network,latency,execution time,and accuracy.

关键词： Healthfog FogBus cascaded convolution neural network cloud computing heart disease automatic health monitoring internet of things

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Elevated Liver Enzymes along with Comorbidity Is a High Risk Factor for COVID-19 Mortality:A South Indian Study on 1,512 Patients

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Journal of Clinical and Translational Hepatology 2022年第1期10卷 120-127页

作者： Narayanasamy Krishnasamy Karthick Rajendran Parimita Barua arunkumar Ramachandran Priyadarshini Panneerselvam Muthukumaran Rajaram Institute of Hepatobiliary Sciences Madras Medical College and Rajiv Gandhi Government General HospitalChennaiTamil NaduIndia Multidisciplinary Research Unit(MRU) Madras Medical CollegeChennaiTamil NaduIndia

Background and Aims:Liver enzyme abnormalities in coronavirus 2019(COVID-19)are being addressed in the *** predictive risk of elevated liver enzymes has not been established for COVID-19 *** this study,we hypothesized that elevated liver enzymes at ad-mission can predict the outcome of COVID-19 disease with other known indicators,such as ***:This retrospective study included all the consecutive hos-pitalized patients with confirmed COVID-19 disease from March 4th to May 31st,*** study was conducted in Rajiv Gandhi Government General Hospital,Chennai,Ta-mil Nadu,*** assessed demography,clinical vari-ables,COVID-19 severity,laboratory parameters,and ***:We included 1,512 patients,and median age was 47 years(interquartile range:34-60)with 36.9%being *** enzyme level(aspartate aminotrans-ferase and/or alanine aminotransferase)was elevated in 450/1,512(29.76%)*** was present in 713/1,512(47.16%)*** with liver enzymes’elevation and presence of comorbidity were older,more frequently hospitalized in ICU and had more severe symp-toms of COVID-19 at the time of *** of liver enzymes’elevation with comorbidity was a high risk factor for death(OR:5.314,95%CI:2.278-12.393),as compared to patients with presence of comorbidity(OR:4.096,95%CI:1.833-9.157).Conclusions:Comorbid-ity combined with liver enzymes’elevation at presentation independently increased the risk of death in COVID-19 by at least 5-fold.

关键词： COVID-19 SARS-CoV-2 Liver enzyme Comorbidity Aspartate aminotransferase Alanine aminotransferase

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A comprehensive assessment on the durability of gas diffusion electrode materials in PEM fuel cell stack

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Frontiers in Energy 2019年第2期13卷 325-338页

作者： arunkumar JAYAKUMAR Mechanical Engineering Department Auckland University of TechnologyAuckland 1142New Zealand Department of Mechatronics Engineering Chennai Institute of TechnologyChennai 600069India

Polymer electrolyte membrane (PEM) fuel cell is the most promising among the various types of fuel cells. Though it has found its applications in numerous fields, the cost and durability are key barriers impeding the commercialization of PEM fuel cell stack. The crucial and expensive component involved in it is the gas diffusion electrode (GDE) and its degradation, which limits the performance and life of the fuel cell stack. A critical analysis and comprehensive understanding of the struc-tural and functional properties of various materials involved in the GDE can help us to address the related durability and cost issues. This paper reviews the key GDE components, and in specific, the root causes influencing the durability. It also envisages the role of novel materials and provides a critical recommendation to improve the GDE durability.

关键词： PEM fuel cell gas diffusion electrode(GDE) gas diffusion layer(GDL) membrane electrode assembly durability fuel cell catalyst

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Vascular-confined multi-passage discoidal nanoconstructs for the low-dose docetaxel inhibition of triple-negative breast cancer growth

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Nano Research 2022年第1期15卷 482-491页

作者： Alessia Felici Daniele Di Mascolo Miguel Ferreira Simone Lauciello Luca Bono Andrea Armirotti arunkumar Pitchaimani Anna Lisa Palange Paolo Decuzzi Laboratory of Nanotechnology for Precision Medicine Fondazione Istituto Italiano di TecnologiaGenoa 16163Italy Department of Informatics BioengineeringRobotics and System EngineeringUniversity of GenoaGenoa 16126Italy Nanochemistry Laboratory Fondazione Istituto Italiano di TecnologiaGenoa 16163Italy Analytical Chemistry Laboratory Fondazione Istituto Italiano di TecnologiaGenoa 16163Italy

Taxane efficacy in triple negative breast cancer(TNBC)is limited by insufficient tumor accumulation and severe off-target *** offer a unique opportunity to enhance the anti-cancer potency of this ***,1,000 nm×400 nm discoidal polymeric nanoconstructs(DPN)encapsulating docetaxel(DTXL)and the near infrared compound Iipid-Cy5 were *** were obtained by filling multiple times cylindrical wells in a poly(vinyl alcohol)template with a polymer mixture comprising poly(lactic-co-glycolic acid)(PLGA)and poly(ethylene glycol)diacrylate(PEG-DA)chains together with therapeutic and imaging *** resulting“multi-passage”DPN exhibited higher DTXL loading,Iipid-Cy5 stability,and stiffness as compared to the conventional"single-passage"*** microscopy confirmed that DTXL-DPN were not taken up by MDA-MB-231 cells but would rather sit next to the cell membrane and slowly release DTXL *** DPN had no toxicity on TNBC cells,whereas DTXL-DPN presented a cytotoxic potential comparable to free DTXL(IC_(50)=2.6 nM±1.0 nM vs.7.0 nM±1.09 nM at 72 h).In orthotopic murine models,DPN accumulated in TNBC more efficiently than *** only 2 mg/kg DTXL,intravenously administered every 2 days for a total of 13 treatments,DTXL-DPN induced tumor regression and were associated to an overall 80%survival rate as opposed to a 30%survival rate for free-DTXL,at 120 *** untreated mice succumbed before 90 ***,this data demonstrates that vascular confined multi-passage DPN,biomimicking the behavior of circulating platelets,can efficiently deliver chemotherapeutic molecules to malignant tissues and effectively treat orthotopic TNBC at minimal taxane doses.

关键词： hydrogel particles template strategy vascular targeting biomimicry cancer therapy

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