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Quantized autoencoder(QAE)intrusion detection system for anomaly detection in resource-constrained loT devices using RT-loT2022 dataset

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Cybersecurity 2024年第2期7卷 13-27页

作者： B S sharmila Rohini Nagapadma Depatment of Electronics and Communication Engineering The National Institute of EngineeringMysoreKarnataka 570008India

In recent years,many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify *** deployment of the unsupervised autoencoder model is computationally expensive in resource-constrained edge *** study proposes quantized autoencoder(QAE)model for intrusion detection systems to detect *** is an optimization model derived from autoencoders that incorporate pruning,clustering,and integer quantization *** autoencoder uint8(QAE-u8)and quantized autoencoder float16(QAE-f16)are two variants of QAE built to deploy computationally expensive Al models into Edge ***,we have generated a Real-Time Internet of Things 2022 dataset for normal and attack *** autoencoder model operates on normal traffic during the training *** same model is then used to reconstruct anomaly traffic under the assumption that the reconstruction error(RE)of the anomaly will be high,which helps to identify the ***,we study the performance of the autoencoders,QAE-u8,and QAE-f16 using accuracy,precision,recall,and F1 score through an extensive experimental *** showed that QAE-u8 outperforms all other models with a reduction of 70.01%in average memory utilization,92.23%in memory size compression,and 27.94%in peak CPU ***,the proposed QAE-u8 model is more suitable for deployment on resource-constrained IoT edge devices.

关键词： IoT constrained system

Juxtapose of System Performance for Food Calorie Estimation Using IoT and Web-based Indagation

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Journal of Harbin Institute of Technology(New Series) 2024年第1期31卷 54-63页

作者： Anusuya S sharmila K Department of Computer Science VISTASChennai 600117India Department of Computer Science Dr.MGR Janaki College for WomenChennai 600028India

A rudimentary aspect of human life is the health of an individual,and most commonly the wellbeing is impacted in a colossal manner through the consumption of food. The intake of calories therefore is a crucial aspect that must be meticulously monitored. Various health gremlins can be largely circumvented when there is a substantial balance in the number of calories ingested versus the quantity of calories *** food calorie estimation is a popular domain of research in recent times and is meticulously analyzed through various image processing and machine learning techniques. However,the need to scrutinize and evaluate the calorie estimation through various platforms and algorithmic approaches aids in providing a deeper insight on the bottlenecks involved,and in improvising the bariatric health of an individual. This paper pivots on comprehending a juxtaposed approach of food calorie estimation through the use of employing Convolution Neural Network(CNN)incorporated in Internet of Things(IoT),and using the Django framework in Python,along with query rule-based training to analyze the subsequent actions to be followed post the consumption of food calories in the constructed webpage. The comparative analysis of the food calorie estimate implemented in both platforms is analyzed for the swiftness of identification,error rate and classification accuracy to appropriately determine the optimal method of use. The simulation results for IoT are carried out using the Raspberry Pi4B model,while the Anaconda prompt is used to run the server holding the web page.

关键词： food calorie estimation convolution neural network Django framework internet of things raspberry Pi

Prediabetes: An overlooked risk factor for major adverse cardiac and cerebrovascular events in atrial fibrillation patients

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World Journal of Diabetes 2024年第1期15卷 24-33页

作者： Rupak Desai Nishanth Katukuri Sumaja Reddy Goguri Azra Kothawala Naga Ruthvika Alle Meena Kumari Bellamkonda Debankur Dey sharmila Ganesan Minakshi Biswas Kuheli Sarkar Pramoda Prattipati Shaylika Chauhan Independent Researcher Independent ResearcherAtlantaGA 30079United States Department of Internal Medicine Mayo ClinicRochesterMN 55902United States Department of Medicine Chalmeda Anand Rao Institute of Medical SciencesTelangana 505001India Department of Medicine Jawaharlal Nehru Medical CollegeBelgaum 590010India Department of Medicine Narayana Medical CollegeAndhra PradeshNellore 524003India Department of Medicine Dr Pinnamaneni Siddhartha Institute of Medical Sciences and Research FoundationVijaywada 521286India Department of Medicine Medical College KolkataKolkata 700073India Department of Medicine P.E.S.Institute of Medical Sciences and ResearchAndhra Pradesh 517425India Department of Medicine Shaheed Ziaur Rahman Medical CollegeBogra 5800Bangladesh Department of Medicine College of Medicine and J.N.M HospitalKalyani 741235India Department of Medicine Jawaharlal Nehru Medical College IndiaKarnatakaBelagavi 590010India Department of Internal Medicine Geisinger Health SystemWikes-BarrePA 18702United States

BACKGROUND Prediabetes is a well-established risk factor for major adverse cardiac and cerebrovascular events(MACCE).However,the relationship between prediabetes and MACCE in atrial fibrillation(AF)patients has not been extensively ***,this study aimed to establish a link between prediabetes and MACCE in AF *** To investigate a link between prediabetes and MACCE in AF *** We used the National Inpatient Sample(2019)and relevant ICD-10 CM codes to identify hospitalizations with AF and categorized them into groups with and without prediabetes,excluding *** primary outcome was MACCE(all-cause inpatient mortality,cardiac arrest including ventricular fibrillation,and stroke)in AF-related *** Of the 2965875 AF-related hospitalizations for MACCE,47505(1.6%)were among patients with *** prediabetes cohort was relatively younger(median 75 vs 78 years),and often consisted of males(56.3%vs 51.4%),blacks(9.8%vs 7.9%),Hispanics(7.3%vs 4.3%),and Asians(4.7%vs 1.6%)than the non-prediabetic cohort(P<0.001).The prediabetes group had significantly higher rates of hypertension,hyperlipidemia,smoking,obesity,drug abuse,prior myocardial infarction,peripheral vascular disease,and hyperthyroidism(all P<0.05).The prediabetes cohort was often discharged routinely(51.1%vs 41.1%),but more frequently required home health care(23.6%vs 21.0%)and had higher *** adjusting for baseline characteristics or comorbidities,the prediabetes cohort with AF admissions showed a higher rate and significantly higher odds of MACCE compared to the non-prediabetic cohort[18.6%vs 14.7%,odds ratio(OR)1.34,95%confidence interval 1.26-1.42,P<0.001].On subgroup analyses,males had a stronger association(aOR 1.43)compared to females(aOR 1.22),whereas on the race-wise comparison,Hispanics(aOR 1.43)and Asians(aOR 1.36)had a stronger association with MACCE with prediabetes vs whites(aOR 1.33)and blacks(aOR 1.21).CONCLUSION This population-

关键词： Prediabetes Atrial fibrillation Cardiovascular disease risk Major adverse cardiovascular and cerebrovascular events Stroke Mortality

Multi-Objective Modified Particle Swarm Optimization for Test Suite Reduction(MOMPSO)

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Computer Systems Science & Engineering 2022年第9期42卷 899-917页

作者： U.Geetha sharmila Sankar Department of Information Technology B.S.Abdur Rahman Crescent Institute of Science and TechnologyChennai600048India Department of Computer Science and Engineering B.S.Abdur Rahman Crescent Institute of Science and TechnologyChennai600048India

Software testing plays a pivotal role in entire software development *** provides researchers with extensive opportunities to develop novel methods for the optimized and cost-effective test suite Although implementation of such a cost-effective test suite with regression testing is being under exploration still it contains lot of challenges and flaws while incorporating with any of the new regression testing algorithm due to irrelevant test cases in the test suite which are not *** kinds of irrelevant test cases might create certain challenges such as code-coverage in the test suite,fault-tolerance,defects due to uncovered-statements and overall-performance at the time of *** this objective,the proposed a new Modified Particle Swarm optimization used for multi-objective test suite *** experiment results involving six subject programs show that MOMPSO method can outer perform with respect to both reduction rate(90.78%to 100%)and failure detection rate(44.56%to 55.01%).Results proved MOMPSO outperformed the other stated algorithms.

关键词： Regression testing test suite reduction test case generation

Reversible Logic Based MOS Current Mode Logic Implementation in Digital Circuits

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Computers, Materials & Continua 2022年第2期70卷 3609-3624页

作者： S.sharmila Devi V.Bhanumathi Department of Electronics and Communication Engineering Sri Ramakrishna Engineering CollegeCoimbatoreIndia Department of Electronics and Communication Engineering Anna UniversityRegional CampusCoimbatoreIndia

Now a days,MOS Current Mode Logic(MCML)has emerged as a better alternative to Complementary Metal Oxide Semiconductor(CMOS)logic in digital *** works have only traditional logic gates that have issues with information *** logic is incorporated with MOS Current Mode Logic(MCML)in this proposed work to solve this problem,which is used for multiplier design,D Flip-Flop(DFF)and *** minimization of power and area is the main aim of the *** reversible logic,the count of outputs and inputs is retained as the same value for creating one-to-one mapping.A unique output vector set can be generated for each input vector set and information loss is also *** reversible MCML based multiplier,reversible logic full adder is utilized to minimize the area and power.D flip-flops based on reversible MCML are often designed to store information that is then combined to form a reversible MCML based *** proposed reversible MCML multiplier attains average power of 0.683 mW,Reversible MCML based DFF achieves 0.56μW and Reversible MCML based 8-bit register attains 04.04μ*** result shows that the proposed Reversible MCML based multiplier,Reversible MCML based D flip-flop and ReversibleMCML based register achieves better performance in terms of current,power dissipation,average power and area.

关键词： MOS current mode logic reversible logic multiplier D flip-flop and register

Optical molecular imaging for detection of Barrett's-associated neoplasia

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World Journal of Gastroenterology 2011年第1期17卷 53-62页

作者： Nadhi Thekkek sharmila Anandasabapathy Rebecca Richards-Kortum Department of Bioengineering Rice UniversityHoustonTX 77005United States Division of Gastroenterology Mount Sinai Medical CenterNew YorkNY 10029United States

Recent advancements in the endoscopic imaging of Barrett's esophagus can be used to probe a wide range of optical properties that are altered with neoplastic *** review summarizes relevant changes in optical properties as well as imaging approaches that measures those ***-field imaging approaches include narrow-band imaging that measures changes in light scattering and absorption,and autofluorescence imaging that measure changes in endogenous ***-resolution imaging approaches include optical coherence tomography,endocytoscopy,confocal microendoscopy,and high-resolution *** technologies,some coupled with an appropriate contrast agent,can measure differences in glandular morphology,nuclear morphology,or vascular alterations associated with *** in targeted contrast agents are further *** that have explored these technologies are highlighted;as are the advantages and limitations of each.

关键词： Barrett's esophagus Barrett's metaplasia Dysplasia Esophageal adenocarcinoma Endoscopy Imaging

Integrated supply chain model for deteriorating item with exponential demand and triangular fuzzy on holding costs

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Journal of Control and Decision 2017年第4期4卷 234-262页

作者： D.sharmila R.Uthayakumar Department of Mathematics The Gandhigram Rural Institute–Deemed UniversityGandhigramIndia

On this paper,we proposed a generalize,incorporated deliver chain model for providers and outlets where delay in bills is obtainable through the suppliers and the shops for consistent deteriorating ***,we provide the mathematical formulations for the trouble beneath have a look at,and then endorse the solution process to derive the top-quality *** here shortages are not *** we projected exponential call for for stores and the *** goal of this paper is to take a look at the stock modeling through fuzzy *** here we use triangular fuzzy range for purchasing the greatest *** an efficient algorithm is developed to decide most useful *** technique is illustrated via a few numerical instance to showcase the utility and the overall performance of the proposed method.

关键词： Exponential demand deterioration distributions integrated model triangular fuzzy fuzzy deterioration

Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries

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Computer Systems Science & Engineering 2023年第5期45卷 1743-1758页

作者： G.sharmila M.K.Kavitha Devi Department of Computer Science&Engineering Syed Ammal Engineering CollegeRamanathapuram623502India Department of Computer Science&Engineering Thiagarajar College of EngineeringMadurai625015India

Over the past era,subgraph mining from a large collection of graph database is a crucial *** addition,scalability is another big problem due to insufficient *** are several security challenges associated with subgraph mining in today’s on-demand *** address this downside,our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs(BCCA-LSDG).The two-fold process is handled in the proposed BCCA-LSDG:graph indexing and authenticated query search(query processing).A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of the proposed *** resolve the issues and provide safe big data transmission,the proposed technique also combines blockchain with a consensus algorithm *** of the big data is ensured by dividing the BC network into distinct networks,each with a restricted number of allowed entities,data kept in the cloud gate server,and data analysis in the *** consensus algorithm is crucial for maintaining the speed,performance and security of the *** Dual Similarity based MapReduce helps in mapping and reducing the relevant subgraphs with the use of optimal feature ***,the graph index refinement process is undertaken to improve the query *** query error,fuzzy logic is used to refine the index of the graph *** proposed technique outperforms advanced methodologies in both blockchain and non-blockchain systems,and the combination of blockchain and subgraph provides a secure communication platform,according to the findings.

关键词： Big data blockchain consensus algorithm trust management graph index

Ext-ICAS:A Novel Self-Normalized Extractive Intra Cosine Attention Similarity Summarization

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Computer Systems Science & Engineering 2023年第4期45卷 377-393页

作者： P.sharmila C.Deisy S.Parthasarathy Deparment of Information Technology Thiagarajar College of EngineeringMaduraiIndia Deparment of Data Science Thiagarajar College of EngineeringMaduraiIndia

With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information *** summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary *** summarization task is framed as seq2seq *** seq2seq methods perform better on short sequences;however,for long sequences,the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this *** novelty is to parallelize the sequence computation training by incorporating feed-forward,the self-normalized neural network in the Extractive phase using Intra Cosine Attention Similarity(Ext-ICAS)with sentence dependency ***,it does not require any normalization technique *** proposed abstractive Bidirectional Long Short Term Memory(Bi-LSTM)encoder sequence model performs better than the Bidirectional Gated Recurrent Unit(Bi-GRU)encoder with minimum training loss and with fast *** proposed model was evaluated on the Cable News Network(CNN)/Daily Mail dataset and an average rouge score of 0.435 was achieved also computational training in the extractive phase was reduced by 59%with an average number of similarity computations.

关键词： Abstractive summarization natural language processing sequence-tosequence learning(seq2seq) self-normalization intra(self)attention