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Identification of crack in a structural member using improved radial basis function(IRBF)neural networks

International Journal of Intelligent Computing and Cybernetics 2013年第2期6卷 182-211页

作者： Rajendra Machavaram shankar Krishnapillai Department of Mechanical Engineering Indian Institute of Technology MadrasChennaiIndia

Purpose–The purpose of this paper is to provide an effective and simple technique to structural damage identification,particularly to identify a crack in a *** neural networks approach is an alternative to identify the extent and location of the damage over the classical *** basis function(RBF)networks are good at function mapping and generalization ability among the various neural network *** neural networks are chosen for the present study of crack ***/methodology/approach–Analyzing the vibration response of a structure is an effective way to monitor its health and even to detect the damage.A novel two-stage improved radial basis function(IRBF)neural network methodology with conventional RBF in the first stage and a reduced search space moving technique in the second stage is proposed to identify the crack in a cantilever beam structure in the frequency *** hypercube sampling(LHS)technique is used in both stages to sample the frequency modal patterns to train the proposed *** is also conducted with and without addition of 5%white noise to the input patterns to simulate the experimental ***–The results show a significant improvement in identifying the location and magnitude of a crack by the proposed IRBF method,in comparison with conventional RBF method and other classical *** case of crack location in a beam,the average identification error over 12 test cases was 0.69 per cent by IRBF network compared to 4.88 per cent by conventional *** improvements are reported when compared to hybrid CPN BPN *** also requires much less computational effort as compared to other hybrid neural network approaches and classical ***/value–The proposed novel IRBF crack identification technique is unique in originality and not reported *** can identify the crack location and crack depth with very good accuracy,less computational effort and ease of imp

关键词： Structures Stress(materials) Mechanical behaviour of materials Beams Structural members Crack identification Structural damage Frequency domain Latin hypercube sampling Improved radial basis function neural networks Reduced search space moving technique

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RGB Based Multiple Share Creation in Visual Cryptography with Aid of Elliptic Curve Cryptography

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China Communications 2017年第2期14卷 118-130页

作者： K.shankar P.Eswaran Department of Computer Science and Engineering Alagappa UniversityKaraikudi-630003Tamil NaduIndia Department of Computer Science and Engineering Alagappa UniversityKaraikudi-630003Tamil NaduIndia

In visual cryptography, many shares are generated which are illogical containing certain message within themselves. When all shares are piled jointly, they tend to expose the secret of the image. The notion of visual secret sharing scheme is to encrypt a secret image into n illogical share images. It is unable to reveal any data on the original image if at least one of the shares is not achieved. The original image, in fact, is realized by overlapping the entire shares directly, in order that the human visual system is competent to identify the collective secret image without employing any complicated computational tools. Therefore, they are communicated steadily as number of shares. The elliptic curve cryptography approach, in turn, is employed to augment the privacy and safety of the image. The *** technique is utilized to generate the multiple shares which are subjected to encryption and decryption by means of the elliptic curve cryptography technique. The test outcomes have revealed the fact that the peak signal to noise ratio is 58.0025, Mean square error value is 0.1164 and the correlation coefficient is 1 for the decrypted image without any sort of distortion of the original image.

关键词： visual cryptography pixel shares elliptic curve cryptography encryption PSNR mean square error

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Decision Tree Based Key Management for Secure Group Communication

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Computer Systems Science & Engineering 2022年第8期42卷 561-575页

作者： P.Parthasarathi S.shankar Department of Computer Science and Engineering Bannari Amman Institute of TechnologySathyamangalam638401India Department of Computer Science and Engineering Hindusthan College of Engineering and TechnologyCoimbatore641032India

Group communication is widely used by most of the emerging network applications like telecommunication,video conferencing,simulation applications,distributed and other interactive *** group communication plays a vital role in case of providing the integrity,authenticity,confidentiality,and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the *** secure group communications,the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service,particularly in the large groups with highly active ***,the paper is aimed to achieve better cost and time efficiency through an improved DC multicast routing protocol which is used to expose the path between the nodes participating in the group *** this process,each node constructs an adaptive Ptolemy decision tree for the purpose of generating the contributory *** of the node is comprised of three keys which will be exchanged between the nodes for considering the group key for the purpose of secure and cost-efficient group *** rekeying process is performed when a member leaves or adds into the *** performance metrics of novel approach is measured depending on the important factors such as computational and communicational cost,rekeying process and formation of the *** is concluded from the study that the technique has reduced the computational and communicational cost of the secure group communication when compared to the other existing methods.

关键词： Key generation adaptive Ptolemy decision tree cost reduction secure group communication

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A stability-indicating LC–MS/MS method for zidovudine: Identification,characterization and toxicity prediction of two major acid degradation products

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Journal of Pharmaceutical Analysis 2017年第4期7卷 231-236页

作者： Prashant S.Devrukhakar M.shiva shankar G.shankar R.Srinivas School of Advance Sciences Vellore Institute of technology (VIT) National Centre for Mass Spectrometry CSIR-Indian Institute of Chemical Technology

Zidvovudine(AZT) is a nucleoside analogue reverse transcriptase inhibitor(NRTI), a class of anti-retroviral drug. A stability-indicating assay method for AZT was developed in line with ICH guideline. Successful separation of AZT and its degradation products was achieved by gradient elution mode on reverse phase C_(18) column using 10 mM ammonium acetate: acetonitrile as the mobile phase at 0.8 mL/min flow rate, 25 μL injection volume, 30 °C column temperature and 285 nm detection wavelength. Two major acid degradation products were identified and characterized by liquid chromatography–electrospray ionization mass spectrometry(LC–ESI/MS/MS) and accurate mass measurements. The probable mechanisms for the formation of degradation products were identified based on a comparison of the fragmentation pattern of the [M + H]^+ions of AZT and its degradation products. One of the degradation products, DP-1, was isolated by semi-preparative high performance liquid chromatography(HPLC) using Waters XBridge Prep C_(18)(250 mm×10 mm, 5 μm).Degradation products showed higher toxicity compared to the drug in some models assessed by TOPKAT software. The method validation was performed with respect to robustness, specificity, linearity, precision and accuracy as per ICH guideline Q2(R1).

关键词： Zidvovudine Stability study Degradation products In-silico toxicity prediction LC–ESI/MS/MS Degradation pathway

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Codimension-2 bifurcation in a discrete predator-prey system with constant yield predator harvesting

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生物数学学报:英文版 2023年第5期16卷 165-191页

作者： Anuraj Singh Vijay shankar Sharma ABV-Indian Institute of Information Technology and Management Gwalior Madhya PradeshIndia

This work investigates the bifurcation analysis in a discrete-time Leslie-Gower predatorprey model with constant yield predator *** stability analysis for the fixed points of the discretized model is shown *** this study,the model undergoes codimension-1 bifurcation such as fold bifurcation(limit point),flip bifurcation(perioddoubling)and Neimark-Sacker bifurcation at a positive fixed ***,the model exhibits codimension-2 bifurcations,including Bogdanov-Takens bifurcation and generalized fip bifurcation at the fixed *** each bifurcation,by using the critical normal form coefficient method,various critical states are *** validate our analytical findings,the bifurcation curves of fixed points are drawn by using *** system exhibits interesting rich dynamics including limit cycles and ***,it has been shown that the predator harvesting may control the chaos in the system.

关键词： Flip bifurcation Neimark-Sacker bifurcation generalized fip bifurcation Bogdanov-Takens bifurcation harvesting

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Semantic Based Greedy Levy Gradient Boosting Algorithm for Phishing Detection

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Computer Systems Science & Engineering 2022年第5期41卷 525-538页

作者： R.Sakunthala Jenni S.shankar Department of Computer Science and Engineering Hindusthan College of Engineering and TechnologyCoimbatore641032India

The detection of phishing and legitimate websites is considered a great challenge for web service providers because the users of such websites are *** websites also create traffic in the entire *** phishing issue is the broadening malware of the entire network,thus highlighting the demand for their detection while massive datasets(i.e.,big data)are *** the application of boosting mechanisms in phishing detection,these methods are prone to significant errors in their output,specifically due to the combination of all website features in the training *** upcoming big data system requires MapReduce,a popular parallel programming,to process massive *** address these issues,a probabilistic latent semantic and greedy levy gradient boosting(PLS-GLGB)algorithm for website phishing detection using MapReduce is proposed.A feature selection-based model is provided using a probabilistic intersective latent semantic preprocessing model to minimize errors in website phishing ***,the missing data in each URL are identified and discarded for further processing to ensure data ***,with the preprocessed features(URLs),feature vectors are updated by the greedy levy divergence gradient(model)that selects the optimal features in the URL and accurately detects the ***,greedy levy efficiently differentiates between phishing websites and legitimate *** are conducted using one of the largest public corpora of a website phish tank *** show that the PLS-GLGB algorithm for website phishing detection outperforms stateof-the-art phishing detection *** amounts of phishing detection time and errors are also saved during the detection of website phishing.

关键词： Web service providers probabilistic intersective latent semantic greedy levy divergence gradient phishing detection big data

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Analysis of Multi-Component Non-Stationary Signals Using Fourier-Bessel Series and Wigner-Hough Transform

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Journal of Electronic Science and Technology 2017年第1期15卷 69-76页

作者： G.Ravi shankar Reddy Rameshwar Rao Department of Electonics and Communication Engineering CVR College of EngineeringHyderabad 501510India Jawaharlal Nehru Technological University Hyderabad 500085India

We presented a novel Fourier-Bessel（FB）series and Wigner-Hough transform（WHT） method for the analysis of multi-component non-stationary *** FB series decomposed multi-component nonstationary signals into mono-component signals. The Wigner-Ville distribution（WVD） was applied to each mono-component signal to analyze its time-frequency distribution（TFD）. Summing up the WVDs of the individual components resulted in TFDs of the multicomponent signals, where the cross terms and noise were significantly reduced. The Hough transform（HT）was applied on the TFD of the multi-component signal（obtained from FB-WVD）. The HT provides an important tool for mapping the signals onto a parameter space where the detection and estimation problems are made easier. This mapping can be used in the detection and parameter estimation of signals which are unknown and embedded in noise.

关键词： decomposed Bessel Wigner stationary overlapping reconstructed chirp priori utilized drawback

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Oscillatory-Plus-Transient Signal Decomposition Using TQWT and MCA

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Journal of Electronic Science and Technology 2019年第2期17卷 135-151页

作者： G. Ravi shankar Reddy Rameshwar Rao Department of Electronics and Communication Engineering CVR College of Engineering Hyderabad 500029 India Jawaharlal Nehru Technological University Hyderabad Hyderabad 500029 India

This paper describes a method for decomposing a signal into the sum of an oscillatory component and a transient component. The process uses the tunable Q-factor wavelet transform (TQWT): The oscillatory component is modeled as a signal that can be sparsely denoted by high Q-factor TQWT;similarly, the transient component is modeled as a piecewise smooth signal that can be sparsely denoted using low Q-factor TQWT. Since the low and high Q-factor TQWT has low coherence, the morphological component analysis (MCA) can effectively decompose the signal into oscillatory and transient components. The corresponding optimization problem of MCA is resolved by the split augmented Lagrangian shrinkage algorithm (SALSA). The applications of the proposed method to speech, electroencephalo-graph (EEG), and electrocardiograph (ECG) signals are included.

关键词： Morphological component analysis (MCA) oscillatory component split augmented Lagrangian shrinkage algorithm (SALSA) transient component tunable Q-factor wavelet transform (TQWT)

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Assessing resource vulnerability quadrants under changing precipitation trends in Uttarakhand,Central Himalayan region

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Journal of Mountain Science 2021年第10期18卷 2722-2741页

作者： Ayushi VLJHANI Vinay shankar Prasad SINHA Mini GOVINDAN Department of Natural Resources TERI School of Advanced Studies10 Institutional AreaVasant Kunj New Delhi 110070India The Energy and Resources Institute India Habitat CentreNew Delhi 110003India

The Central Himalayan region is vulnerable to the adverse effects of climate change and characterized by regional climatic *** livelihood of the mountain communities across the Himalaya is at risk owing to the consequences of variable precipitation *** exists limited empirical research on precipitation variability due to inadequate hydro-meteorological stations at highaltitude *** study uses a novel methodology which integrates precipitation variability with resource sensitivity over the three verticals of Central Himalaya:Himadri,Himachal and shivaliks and across four major river basins:Yamuna,Upper Ganga,Ghaghar and *** magnitude of the significant precipitation trends was estimated through time series analysis at a 95%confidence *** assess the sensitivity of natural resources(forest,water and land)and human resources,fourteen mountain-specific indicators were identified which captured resource index using data standardization and principal component ***’s slope and Resource index were plotted in a 2D Cartesian coordinate to draw precipitation-resource quadrants with their effective coverage area:High Precipitation and Scarce Resources(35.92%);Low Precipitation and Abundant Resources(30.10%);Low Precipitation and Scarce Resources(22.33%)and High Precipitation and Abundant Resources(11.65%).This helped in developing quadrant-specific adaptation strategies under regional variability of *** methodology and the research findings will certainly assist water experts,resource managers and policy makers to strengthen adaptive capacity and improve the resilience of vulnerable communities across Himalaya.

关键词： Climate Change Trend analysis Resource-quadrant Vulnerability Adaptation Central Himalaya

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Optimal Data Placement and Replication Approach for SIoT with Edge

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Computer Systems Science & Engineering 2022年第5期41卷 661-676页

作者： B.Prabhu shankar S.Chitra Department of Information Technology Er Perumal Manimekalai College of EngineeringHosur635117TamilnaduIndia Department of Computer Science and Engineering Er Perumal Manimekalai College of EngineeringHosur63117TamilnaduIndia

Social networks(SNs)are sources with extreme number of users around the world who are all sharing data like images,audio,and video to their friends using IoT *** concept is the so-called Social Internet of Things(SIot).The evolving nature of edge-cloud computing has enabled storage of a large volume of data from various sources,and this task demands an efficient storage *** this kind of large volume of data storage,the usage of data replication using edge with geo-distributed cloud service area is suited to fulfill the user’s expectations with low *** major issue is the way to store the data and replicate these large data items optimally and allocate the request from the data center *** efficient storage of these data,we use edge server,which is part of the cloud server,in this ***,the data are distributed and stored with quick access,which will reduce the latency with *** proposed data placement approach learns with machine learning(ML)algorithm called radial basis kernel function assisted with support vector machine(RBF-SVM)to classify the data center for storing the user and friend’s data from the SIoT *** learning algorithms will be used to predict the workload of the data stored in the data center as either edge or cloud depending on the existing time *** data placement with dynamic nature is also optimized using the proposed dynamic graph partitioning(GP)method to meet the individual user’s demand of low latency with minimum *** way will keep the SIoT data placement efficient and effective over ***,this proposed data placement and replication approach introduces three kinds of innovations compared with the existing data placement approach.(i)Rather than storing the user data in a single cloud,this study uses the edge server closest to the SIoT devices for faster access with reduced response time.(ii)The classification algorithm called RBF-SVM is used to find storage for

关键词： Data placement data replication social network social internet of things edge computing cloud computing graph partitioning support vector machine machine learning radial basis function latency storage cost

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