检索结果-南通市图书馆

Design of Hybrid True Random Number Generator for Cryptographic Applications

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer systems science & Engineering 2022年第11期43卷 423-437页

作者： s.nithya Devi s.sasipriya Electronics and Communication Engineering Dr.N.G.P.Institute of TechnologyCoimbatore641110India Electronics and Communication Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India

In real-time applications,unpredictable random numbers play a major role in providing cryptographic and encryption *** of the existing random number generators are embedded with the complex nature of an amplifier,ring oscillators,or ***,this research focused more on implementing a Hybrid Nature of a New Random Number *** key objective of the proposed methodology relies on the utilization of True random number *** randomness is *** additions of programmable delay lines will reduce the processing time and maintain the quality of *** performance comparisons are carried out with power,delay,and lookup *** proposed architecture was executed and verified using *** Hybrid TRNG is evaluated under simulation and the obtained results outperform the results of the conventional random generators based on slices,area and Lookup *** experimental observations show that the proposed Hybrid True Random Number Generator(HTRNG)offers high operating speed and low power consumption.

关键词： True random number generators lookup table random number generator digital circuit seed

Metric and Upper Dimension of Extended Annihilating-Ideal Graphs

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Algebra Colloquium 2024年第2期31卷 221-238页

作者： s.nithya G.Elavarasi Genghua Fan Department of Mathematics St.Xavier's College(Autonomous)Palayamkottai 627002Tamil NaduIndia Afiliated to Manonmaniam sundaranar University Abishekapatti Tirunelveli 627012Tamil NaduIndia PG and Research Department of Mathematics St.Xavier's College(Autonomous)Palayamkottai 627002Tamil NaduIndia Affiliated to Manonmaniam sundaranar University Abishekapatti Tirunelveli 627012Tamil NaduIndia 不详

The metric dimension problem is called navigation problem due to its application to robot navigation in *** this concept has wide applications in motion planning,sonar and loran station,and so *** this paper,we study certain results on the metric dimension,upper dimension and resolving number of extended annihilating-ideal graph EAG(R)associated to a commutative ring R,denoted by dim M(EAG(R)),dim+(EAG(R))and res(EAG(R)),*** we prove the finiteness conditions of dim M(EAG(R))and dim+(EAG(R)).In addition,we characterize dim M(EAG(R)),dim+(EAG(R))and res(EAG(R))for artinian rings and the direct product of rings.

关键词： extended annihilating-ideal graph metric dimension upper dimension resolving number

Metaheuristic secure Clustering scheme for Energy Harvesting Wireless sensor Networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer systems science & Engineering 2023年第4期45卷 497-512页

作者： s.nithya Roopa P.Anandababu sibi Amaran Rajesh Verma Department of Computer science and Engineering Kumaraguru College of TechnologyCoimbatore641049India Department of Computer and Information science Faculty of ScienceAnnamalai UniversityChidambaram608002India Department of Computing Technologies SRM Institute of Science and TechnologyChennai603203India Department of Electrical Engineering King Khalid UniversityAbha61411Kingdom of Saudi Arabia

Recently,energy harvesting wireless sensor networks(EHWsN)have increased significant attention among research *** harvesting energy from the neighboring environment,the sensors in EHWsN resolve the energy constraint problem and offers lengthened network *** is one of the proficient ways for accomplishing even improved lifetime in *** clustering process intends to appropriately elect the cluster heads(CHs)and construct *** several models are available in the literature,it is still needed to accomplish energy efficiency and security in *** this view,this study develops a novel Chaotic Rider Optimization Based Clustering Protocol for secure Energy Harvesting Wireless sensor Networks(CROC-sEHWsN)*** presented CROC-sEHWsN model aims to accomplish energy efficiency by clustering the node in *** CROC-sEHWsN model is based on the integration of chaotic concepts with traditional rider optimization(RO)***,the CROC-sEHWsN model derives a fitness function(FF)involving seven distinct parameters connected to *** accomplish security,trust factor and link quality metrics are considered in the *** design of RO algorithm for secure clustering process shows the novelty of the *** order to demonstrate the enhanced performance of the CROC-sEHWsN approach,a wide range of simulations are carried out and the outcomes are inspected in distinct *** experimental outcome demonstrated the superior performance of the CROC-sEHWsN technique on the recent approaches with maximum network lifetime of 387.40 and 393.30 s under two scenarios.

关键词： Clustering wireless sensor networks network lifetime energy efficiency metaheuristics energy harvesting rider optimization

An Adaptive Classifier Based Approach for Crowd Anomaly Detection

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第7期72卷 349-364页

作者： sofia Nishath P.s.nithya Darisini school of Computer science and Engineering Vellore Institute of TechnologyChennai600127India

Crowd Anomaly Detection has become a challenge in intelligent video surveillance system and *** video surveillance systems make extensive use of data mining,machine learning and deep learning *** this paper a novel approach is proposed to identify abnormal occurrences in crowded situations using deep *** this approach,Adaptive GoogleNet Neural Network Classifier with Multi-Objective Whale Optimization Algorithm are applied to predict the abnormal video frames in the crowded *** use multiple instance learning(MIL)to dynamically develop a deep anomalous ranking *** technique predicts higher anomalous values for abnormal video frames by treating regular and irregular video bags and video *** use the multi-objective whale optimization algorithm to optimize the entire process and get the best *** performance parameters such as accuracy,precision,recall,and F-score are considered to evaluate the proposed technique using the Python simulation *** simulation results show that the proposed method performs better than the conventional methods on the public live video dataset.

关键词： Abnormal event detection adaptive GoogleNet neural network classifier multiple instance learning multi-objective whale optimization algorithm

Data Analytics on Unpredictable Pregnancy Data Records Using Ensemble Neuro-Fuzzy Techniques

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer systems science & Engineering 2023年第8期46卷 2159-2175页

作者： C.Vairavel N.s.nithya Faculty of Information and Communication Engineering Anna UniversityChennai600025India Department of Computer science and Engineering KSR College of EngineeringTiruchengode637215India

The immune system goes through a profound transformation during pregnancy,and certain unexpected maternal complications have been correlated to this *** ability to correctly examine,diagnoses,and predict pregnancy-hastened diseases via the available big data is a delicate problem since the range of information continuously increases and is *** approaches for disease diagnosis/classification have been established with the use of data mining ***,such methods do not provide an appropriate classification/diagnosis ***,single learning approaches are used to create the bulk of these *** issues may be made more accurate by combining predictions from many different *** a result,we used the Ensembling of Neuro-Fuzzy(E-NF)method to perform a high-level classification of medical diseases.E-NF is a layered computational model with self-learning and self-adaptive capabilities to deal with specific problems,such as the handling of imprecise and ambiguous data that may lead to uncertainty concerns that specifically emerge during the classification *** data,Training phase,Ensemble phase,and Testing phase make up the complete procedure for the suggested *** preprocessing includes feature extraction and dimensionality *** such processes,the training phase includes the fuzzification process of medical ***,training of input data was done using four types of NF techniques:Fuzzy Adaptive Learning Control Network(FALCON),Adaptive Network-based Fuzzy Inference system(ANFIs),self Constructing Neural Fuzzy Inference Network(sONFIN)and/Evolving Fuzzy Neural Network(EFuNN).Later,in the ensemble phase,all the NF methods’predicted outcomes are integrated,and finally,the test results are evaluated in the testing *** outcomes indicate that the method could predict impaired glucose tolerance,preeclampsia,gestational hypertensive abnormalities,bacteriuria,and iron deficien

关键词： Pregnancy disorders ensemble neuro-fuzzy accuracy diagnostics impaired glucose tolerance and preeclampsia gestational hypertension abnormalities bacteriuria iron deficiency anaemia

Evaluating Ignition and Combustion Performance with Al-Metal- Organic Frameworks and Nano-Aluminum in HTPB Fuel

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

火炸药学报 2024年第5期47卷 413-421,I0003页

作者： sri nithya Mahottamananda Yash Pal Yarravarapu sai sriram subha s Djalal Trache Department of Aerospace Engineering B S Abdur Rahman CrescentInstitute of Science and TechnologyChennai-600048India school of Aeronautical science Hindustan Institute of Technologyand ScienceChennai-603103India Energetic Materials Laboratory(EMLab) Teaching and ResearchUnit of Energetic ProcessesEcole Militaire PolytechniqueBP 17Bordj El-Bahri16046AlgiersAlgeria

Incorporating aluminum metal-organic frameworks(Al-MOFs)as energetic additives for solid fuels presents a promising avenue for enhancing combustion *** study explores the potential benefits of Al-MOF(MIL-53(Al))energetic additive on the combustion performance of hydroxyl-terminated polybutadiene(HTPB)*** HTPB-MOF fuel samples were manufactured using the vacuum-casting technique,followed by a comprehensive evaluation of their ignition and combustion properties using an opposed flow burner(OFB)setup utilizing gaseous oxygen as an *** gauge the effectiveness of Al-MOFs as fuel additives,their impact is compared with that of nano-aluminum(nAl),another traditional additive in HTPB *** results indicate that the addition of 15%(mass fraction)nAl into HTPB resulted in the shortest ignition delay time(136 ms),demonstrating improved ignition performance compared to pure HTPB(273 ms).The incorporation of Al-MOF in HTPB also reduced ignition delay times to 227 ms and 189 ms,***,under high oxidizer mass flux conditions(79—81 kg/(m^(2)s)),HTPB fuel with 15%nAl exhibited a substantial 83.2%increase in regression rate compared to the baseline HTPB fuel,highlighting the positive influence of nAl on combustion *** contrast,HTPB-MOF with a 15%Al-MOF additive showed a 32.7%increase in regression rate compared to pure *** results suggest that HTPB-nAl outperforms HTPB-MOF in terms of regression rates,indicating a more vigorous and rapid burning behavior.

关键词： ignition combustion enhancement MOF HTPB regression rate

Ensemble Deep Learning for IoT Based COVID 19 Health Care Pollution Monitor

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Intelligent Automation & soft Computing 2023年第2期35卷 2383-2398页

作者： nithya Rekha sivakumar Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Internet of things(IoT)has brought a greater transformation in health-care sector thereby improving patient care,minimizing treatment *** pre-sent method employs classical mechanisms for extracting features and a regression model for *** methods have failed to consider the pollu-tion aspects involved during COVID 19 *** Ensemble Deep Learning and Framingham Feature Extraction(FFE)techniques,a smart health-care system is introduced for COVID-19 pandemic disease *** Col-lected feature or data via predictive mechanisms to form pollution *** maps are used to implement real-time countermeasures,such as storing the extracted data or feature in a Cloud server to minimize concentrations of air *** integrated with patient management systems,this solution would minimize pollution emitted via patient’s sensors by offering spaces in the cloud server when pollution thresholds are ***,the Gini Index factor infor-mation gain technique eliminates unimportant and redundant attributes while selecting the most relevant,reducing computing overhead and optimizing system ***,the COVID-19 disease prognosis ensemble deep learning-based classiﬁer is *** analysis is planned to measure the prediction accuracy,error,precision and recall for different numbers of *** results show that prediction accuracy is improved by 8%,error rate was reduced by 47%and prediction time is minimized by 36%compared to exist-ing methods.

关键词： Internet of Things Covid-19 ensemble deep learning framingham feature extraction

A TimeImageNet sequence Learning for Remaining Useful Life Estimation of Turbofan Engine in Aircraft systems

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

structural Durability & Health Monitoring 2021年第4期15卷 317-334页

作者： s.kalyani K.Venkata Rao A.Mary sowjanya Department of Computer science&systems Engineering Andhra University College of Engineering(A)VisakhapatnamIndia

Internet of Things systems generate a large amount of sensor data that needs to be analyzed for extracting useful insights on the health status of the machine under *** data of all possible states of a system are used for building machine learning *** models are further used to predict the possible downtime for proactive action on the system *** engine data from run to failure is used in the current *** run to failure data includes states like new installation,stable operation,first reported issue,erroneous operation,and final *** the present work,the non-linear multivariate sensor data is used to understand the health status and anomalous *** methodology is based on different sampling sizes to obtain optimum results with great *** time series of each sensor is converted to a 2D image with a specific time *** Images would represent the health of a system in higher-dimensional *** created images were fed to Convolutional Neural Network,which includes both time variation and space variation of each sensed *** these created images,a model for estimating the remaining life of the aircraft is ***,the proposed net is also used for predicting the number of engines that would fail in the given time *** current methodology is useful in avoiding the health index generation for predicting the remaining useful life of the industrial *** accuracy in the classification of components is achieved using the TimeImagenet-based approach.

关键词： Multivariate sensor data TimeImageNet Remaining life estimation machine learning 2D image Convolutional Neural Network

Unraveling the role of dual Ti/Mg metals on the ignition and combustion behavior of HTPB-boron-based fuel

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Defence Technology（防务技术） 2024年第2期32卷 134-143页

作者： Arijit Debnath Yash Pal sri nithya Mahottamananda Djalal Trache school of Aeronautical science Hindustan Institute of Technology and ScienceChennai 603103India Department of Aerospace Engineering B S Abdur Rahman Crescent Institute of Science and TechnologyChennai 600048India Energetic Materials Laboratory(EMLab) Teaching and Research Unit of Energetic ProcessesEcole Militaire PolytechniqueBP 17Bordj El-Bahri16046AlgiersAlgeria

Metal additives play an essential role in explosive and propellant formulations. Boron(B) is widely used in propellant applications owing to its high energetic content. The addition of B to explosives and propellants increases their energy density, making them more efficient and powerful. Nevertheless, B forms oxide layers on its surface during combustion, slowing down the combustion rate and reducing rocket motor efficiency. To overcome this issue, other metal additives such as aluminum(Al), magnesium(Mg),and titanium(Ti) are revealed to be effective in boosting the combustion rate of propellants. These additives may improve the combustion rate and therefore enhance the rocket motor’s performance. The present study focused on preparing and investigating the ignition and combustion behavior of pure hydroxyl-terminated polybutadiene(HTPB)-B fuel supplemented with nano-titanium and nanomagnesium. The burn rates of HTPB-B fuel samples were evaluated on the opposed flow burner(OFB)under a gaseous oxygen oxidizer, for which the mass flux ranges from 22 kg/(m^(2)·s) to 86 kg/(m^(2)·s). The addition of Ti and Mg exhibited higher regression rates, which were attributed to the improved oxidation reaction of B due to the synergetic metal combustion effect. The possible combustion/oxidation reaction mechanism of B-Mg and B-Ti by heating the fuel samples at 900℃ and 1100℃ was also examined in a Nabertherm burnout furnace under an oxygen atmosphere. The post-combustion products were collected and further subjected to X-ray diffraction(XRD) and field emission scanning electron microscopy(FE-sEM) analyses to inspect the combustion behavior of B-Ti and B-Mg. It has been observed that the B oxide layer at the interface between B-Ti(B-Mg) is removed at lower temperatures, hence facilitating oxygen transfer from the surroundings to the core B. Additionally, Ti and Mg decreased the ignition delay time of B, which improved its combustion performance.

关键词： Boron B_(2)O_(3) Opposed flow burner Combustion Magnesium