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Low-Level Antibiotic Resistance among Staphylococcus aureus and Gram-Negative pathogens from Infected Skin and Soft Tissues in Rural Kenya

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Open Journal of Medical Microbiology 2024年第1期14卷 23-38页

作者： Justin Nyasinga Zubair Munshi Lillian Musila Ephantus Mbugua Geoffrey Omuse Gunturu revathi Department of pathology Aga Khan University Nairobi Kenya Department of Biomedical Sciences and Technology Technical University of Kenya Nairobi Kenya Institute of Science Technology and Innovation Pan-African University Nairobi Kenya United States Army Medical Research Directorate—Africa Nairobi Kenya

Introduction: Bacterial skin and soft tissue infections (SSTIs) are a cause of frequent inpatient and outpatient care visits whose causative agents are associated with a high antimicrobial resistance burden. For insights on antimicrobial susceptibilities in a rural setting, we examined specimens from suspected SSTIs from two public health facilities in Kenya. We additionally assessed antibiotic use, appropriateness of empiric therapy and risk factors for SSTI. Methodology: Between 2021 and 2023, 265 patients at Kisii and Nyamira County Referral hospitals were enrolled. Wound swabs/aspirates were collected and processed following standard microbiological procedures. Identification and antimicrobial susceptibility were performed using the VITEK 2 Compact platform. Demographic, clinical, and microbiological data were analyzed with R Statistical software. Results: S. aureus was isolated in 16.2% (43/265) of patients with a methicillin resistance (MRSA) proportion of 14% (6/43). While 13/15 drugs elicited susceptibilities ranging from 84% - 100%, penicillin (16%) and trimethoprim-sulfamethoxazole [TMp-SXT] (23%) yielded the lowest susceptibilities. Escherichia coli (n = 33), Klebsiella pneumoniae (n = 8), pseudomonas aeruginosa (n = 8), and Citrobacter species (n = 4) were the most commonly isolated gram-negative species. Gram-negative strains showed high susceptibilities to most of the tested drugs (71% - 100%) with the exception of ampicillin (18%), TMp-SXT (33%), and first and second generation cephalosporins. Conclusions: The low MRSA prevalence and generally high antibiotic susceptibilities for S. aureus and gram-negative bacteria present opportunities for antibiotic stewardship in the study setting. Diminished susceptibilities against penicillin/ampicillin and TMp-SXT accord with prevailing local data and add a layer of evidence for their cautious empiric use.

关键词： S. aureus MRSA Gram-Negative Bacteria Antimicrobial Resistance SSTIs Kenya

Randomized MILp framework for Securing Virtual Machines from Malware Attacks

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Intelligent Automation & Soft Computing 2023年第2期35卷 1565-1580页

作者： R.Mangalagowri revathi Venkataraman Computer Science Department SRM Institute of Science and TechnologyKattankulathurTamil Nadu603203India School of Computing SRM Institute of Science and TechnologyKattankulathurTamil Nadu603203India

Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational *** Machines(VMs)are supplied on requests and launched without interactions from service *** can target these servers and establish malicious con-nections on VMs for carrying out attacks on other clustered *** existing system has issues with execution time and false-positive ***,the overall system performance is degraded *** proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain *** request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s *** of SECURITY Resources accepts a safety game in a simple format as input andﬁnds the best coverage vector for the opponent using a Stackelberg Equilibrium(SSE)technique.A Mixed Integer Linear programming(MILp)framework is used in the *** VM challenge is reduced by aﬁrewall-based controlling mechanism combining behavior-based detection and signature-based virus *** pro-posed method is focused on detecting malware attacks effectively and providing better security for the ***,the experimental results indicate that the pro-posed security method is efﬁ*** consumes minimum execution time,better false positive rate,accuracy,and memory usage than the conventional approach.

关键词： Virtualization technology security cross-VM channel attack VM-escape R-VM-MILp algorithm(randomized VM allocation of security resources) Mixed Integer Linear programming(MILp) SSE strategy ﬁrewall-based monitoring method

Hybrid Authentication Using Node Trustworthy to Detect Vulnerable Nodes

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Computer Systems Science & Engineering 2023年第4期45卷 625-640页

作者： S.M.Udhaya Sankar S.Thanga revathi R.Thiagarajan Department of Information Technology Velammal Insitutue of TechnologyChennai601204India Department of Networking and Communication SRM Institute of Science and TechnologyKattankulathur603203India Department of Information Technology Prathyusha Engineering CollegeThiruvallur602025India

An ad-hoc sensor network(ASN)is a group of sensing nodes that transmit data over a wireless link to a target node,direct or indirect,through a series of *** becomes a high-risk group for several security exploits due to the sensor node’s limited *** threats are more challenging to protect against than external *** nodes are grouped,and calculate each node’s trust *** trust level is the result of combining internal and external trust *** heads(CH)are chosen based on the anticipated trust *** communications are then digitally signed by the source,encoded using a key pair given by a trustworthy CH,decoded by the recipient,and supervised by *** authenticates the technique by identifying the presence of both the transmitter and the *** approach looks for a trustworthy neighboring node that meets the trust threshold condition to authenticate the key *** companion node reaffirms the node’s reliability by getting the public-key *** seeking sensor node and the certification issuer node must have a close and trusting *** results of the proposed hybrid authentication using a node trustworthy(HANT)system are modeled and tested,and the suggested approach outperforms conventional trust-based approaches in throughput,latency,lifetime,and vulnerability methods.

关键词： Ad hoc sensor network wireless security clustering cryptography key management

Optimal IoT Based Improved Deep Learning Model for Medical Image Classification

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Computers, Materials & Continua 2022年第11期73卷 2275-2291页

作者： prasanalakshmi Balaji B.Sri revathi praveetha Gobinathan Shermin Shamsudheen Thavavel Vaiyapuri Department of Computer Science King Khalid UniversitySaudi Arabia School of Electrical Engineering Vellore Institute of TechnologyIndia Department of Computer Science Jazan UniversitySaudi Arabia College of Computer Engineering and Science Prince Sattam bin Abdulaziz UniversitySaudi Arabia

Recently medical image classification plays a vital role in medical image retrieval and computer-aided diagnosis *** deep learning has proved to be superior to previous approaches that depend on handcrafted features;it remains difficult to implement because of the high intra-class variance and inter-class similarity generated by the wide range of imaging modalities and clinical *** Internet of Things(IoT)in healthcare systems is quickly becoming a viable alternative for delivering high-quality medical treatment in today’s e-healthcare *** recent years,the Internet of Things(IoT)has been identified as one of the most interesting research subjects in the field of health care,notably in the field of medical image *** medical picture analysis,researchers used a combination of machine and deep learning techniques as well as artificial *** newly discovered approaches are employed to determine diseases,which may aid medical specialists in disease diagnosis at an earlier stage,giving precise,reliable,efficient,and timely results,and lowering death *** on this insight,a novel optimal IoT-based improved deep learning model named optimization-driven deep belief neural network(ODBNN)is proposed in this *** context,primarily image quality enhancement procedures like noise removal and contrast normalization are *** the preprocessed image is subjected to feature extraction techniques in which intensity histogram,an average pixel of RGB channels,first-order statistics,Grey Level Co-Occurrence Matrix,Discrete Wavelet Transform,and Local Binary pattern measures are *** extracting these sets of features,the May Fly optimization technique is adopted to select the most relevant *** selected features are fed into the proposed classification algorithm in terms of classifying similar input images into similar *** proposed model is evaluated in terms of accuracy,precision,recall,and f-

关键词： Deep belief neural network mayfly optimization gaussian filter contrast normalization grey level variance local binary pattern discrete wavelet transform

RMCARTAM For DDoS Attack Mitigation in SDN Using Machine Learning

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Computer Systems Science & Engineering 2023年第6期45卷 3023-3036页

作者： M.revathi V.V.Ramalingam B.Amutha Department of Computing Technologies SRM Institute of Science and TechnologyKattankulathurChennai603203Tamil NaduIndia

The impact of a Distributed Denial of Service(DDoS)attack on Soft-ware Defined Networks(SDN)is briefly *** approaches to detecting DDoS attacks exist,varying on the feature being considered and the method ***,the methods have a deficiency in the performance of detecting DDoS attacks and mitigating *** improve the performance of SDN,an efficient Real-time Multi-Constrained Adaptive Replication and Traffic Approximation Model(RMCARTAM)is sketched in this *** RMCARTAM considers different parameters or constraints in running different controllers responsible for handling incoming *** model is designed with multiple controllers to handle net-work traffic but can turn the controllers according to *** multi-con-straint adaptive replication model monitors different features of network traffic like rate of packet reception,class-based packet reception and target-specific *** to these features,the method estimates the Replication Turn-ing Weight(RTW)based on which triggering controllers are ***,the method applies Traffic Approximation(TA)in the detection of DDoS *** detection of a DDoS attack is performed by approximating the incoming traf-fic to any service and using various features like hop count,payload,service fre-quency,and malformed frequency to compute various support measures on bandwidth access,data support,frequency support,malformed support,route sup-port,and so *** all these support measures,the method computes the value of legitimate weight to conclude the behavior of any source in identifying the mal-icious *** node details are used in the mitigation of DDoS *** method stimulates the network performance by reducing the power factor by switching the controller according to different factors,which also reduces the *** the same way,the proposed model improves the accuracy of detecting DDoS attacks by estimating the features of incoming traffic in

关键词： DDoS SDN traffic approximation adaptive replication multi-controller support measures RTW

Fuzzy Based Reliable Load Balanced Routing Approach for Ad hoc Sensor Networks

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Computer Systems Science & Engineering 2022年第6期41卷 861-874页

作者： J.V.Anchitaalagammai Rajesh Verma M.Kavitha A.R.revathi S.R.preethi Kiranmai Bellam Department of Computer Science and Engineering Velammal College of Engineering and TechnologyMadurai625009TamilNaduIndia Department of Electrical Engineering King Khalid UniversityAbha62529Saudi Arabia Department of Electronics and Communication Engineering K.Ramakrishnan College of TechnologyTiruchirappalli621112Tamil NaduIndia Department of Information Technology SRM Valliammai Engineering CollegeChennai603203Tamil NaduIndia Department of Electronics and Communication Engineering SRM Valliammai Engineering CollegeChennai603203Tamil NaduIndia Department of Computer Science Prairie View A&M UniversityPrairie ViewTXUnited State

Energy management and packet delivery rate are the important factors in ad hoc *** is the major network where nodes share the information without *** to the mobility of nodes,maximum energy is spent on transmission of *** energy is wasted on packet dropping and false route *** this research work,Fuzzy Based Reliable Load Balanced Routing Approach(RLRA)is proposed to provide high energy efficiency and more network lifetime using optimal multicast route discovery *** contains three *** first phase,optimal multicast route discovery is initiated to resolve the link *** second phase,the link quality is estimated and set to threshold value to meet the requirements of high energy *** third phase,energy model is shown to obtain total energy of network after transmission of packets.A multicast routing is established Based on path reliability and fault tolerant calculation is done and integrated with multicast *** routes can withstand the malicious *** decision model is integrated with propose protocol to decide the performance of network *** network simulation tool is used for evaluating the RLRA with existing schemes and performance of RLRA is good compared to others.

关键词： Fuzzy model link quality multicast route energy model cluster group node lifetime

SDN-based intrusion detection system for IoT using deep learning classifier (IDSIoT-SDL)

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CAAI Transactions on Intelligence Technology 2021年第3期6卷 281-290页

作者： Azka Wani revathi S Rubeena Khaliq Department of Computer Applications Crescent B S Abdur Rahman Institute of Science and TechnologyChennaiIndia Department of Computer Science and Engineering Crescent B S Abdur Rahman Institute of Science and TechnologyChennaiIndia Department of Mathematics Crescent B S Abdur Rahman Institute of Science and TechnologyChennaiIndia

The participation of ordinary devices in networking has created a world of connected devices *** Internet of Things(IoT)includes heterogeneous devices from every *** are no definite protocols or standards for IoT communication,and most of the IoT devices have limited *** a complete security measure for such devices is a challenging task,yet *** lightweight security solutions have surfaced lately for *** lightweight security protocols are unable to provide an optimum protection against prevailing powerful threats in cyber *** is also hard to deploy any traditional security protocol on resource-constrained IoT ***-defined networking introduces a centralized control in computer *** has a programmable approach towards networking that decouples control and data *** SDN-based intrusion detection system is proposed which uses deep learning classifier for detection of anomalies in *** proposed intrusion detection system does not burden the IoT devices with security *** proposed work is executed on the simulated *** results of the simulation test are evaluated using various matrices and compared with other relevant methods.

关键词： IoT classifier system

Review of Computational Techniques for the Analysis of Abnormal patterns of ECG Signal provoked by Cardiac Disease

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Computer Modeling in Engineering & Sciences 2021年第9期127卷 875-906页

作者： revathi Jothiramalingam Anitha Jude Duraisamy Jude Hemanth Kalaignarkarunanidhi Institute of Technology Coimbatore641402India Department of ECE Karunya Institute of Technology and SciencesCoimbatore641114India

The 12-lead ECG aids in the diagnosis of myocardial infarction and is helpful in the prediction of cardiovascular disease *** does,though,have certain *** other electrocardiographic anomalies such as Left Bundle Branch Block and Left Ventricular Hypertrophy syndrome,the ECG signal withMyocardial Infarction is difficult to *** diseases cause variations in the ST portion of the ECG *** reduces the clarity of ECG signals,making itmore difficult to diagnose these *** a result,the specialist is misled into making an erroneous diagnosis by using the incorrect therapeutic *** on these concepts,this article reviews the different procedures involved in ECG signal pre-processing,feature extraction,feature selection,and classification techniques to diagnose heart disorders such as LeftVentricularHypertrophy,Bundle Branch Block,andMyocardial *** reveals the flaws and benefits in each segment,as well as recommendations for developing more advanced and robustmethods for diagnosing these diseases,which will increase the system’s *** current issues and prospective research directions are also addressed.

关键词： Bundle branch block myocardial infarction left ventricular hypertrophy feature selection feature extraction classification

Quantum Chemical Vibrational Study, FTIR and FT-Raman Spectra of 1,3-Diphenyl propenone

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光谱学与光谱分析 2019年第12期39卷 3932-3939页

作者： revathi Haldorai M.Thirumalaikumar S.Sampathkrishnan C.Charanya N.Balamurugan Department of Chemistry Karpagam Academy of Higher EducationEachanariCoimbatore641021Tamil NaduIndia Department of Applied Chemistry Sri Venkateswara College of EngineeringSriperumbudur602105Tamil NaduIndia Department of Applied physics Sri Venkateswara College of EngineeringSriperumbudur602105Tamil NaduIndia Research Scholar Department of Applied PhysicsSri Venkateshwara College of EngineeringSriperumbudur 602105TamilnaduIndia Department of physics Dhanalakshmi College of EngineeringTambaramChennaiTamilnaduIndia

The Fourier Transform Infrared(FTIR)and Fourier transform Raman(FT-Raman)spectra of 1,3-Diphenyl propenone were recorded in the regions 4000~400 and 4000~100 cm^-1,respectively,in the solid *** electronic energy,geometrical structure,harmonic vibrational spectra was computed at the DFT/6-31G(d,p)and three parameter hybrid functional Lee-Yang-parr/6-31G(d,p)levels of *** vibrational studies were interpreted in terms of potential energy distribution(pED).The results were compared with experimental values with the help of scaling *** of the modes have wave numbers in the expected range and are in good agreement with computed values and also the molecular properties of Mulliken population analysis have been ***,thermodynamic properties were performed.

关键词： FTIR FT-Raman Vibrational spectra pED