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Applied Mathematics(A Journal of Chinese Universities) 2019年第2期34卷 229-252页

作者： J Dhivya B sridevi Department of Mathematics Kumaraguru College of TechnologyCoimbatoreTamil NaduIndia Department of Mathematics PSG College of TechnologyCoimbatoreTamil NaduIndia

Similarity measure is an essential tool to compare and determine the degree of similarity between intuitionistic fuzzy sets (IFSs). In this paper, a new similarity measure between intuitionistic fuzzy sets based on the mid points of transformed triangular fuzzy numbers is proposed. The proposed similarity measure provides reasonable results not only for the sets available in the literature but also gives very reasonable results, especially for fuzzy sets as well as for most intuitionistic fuzzy sets. To provide supportive evidence, the proposed similarity measure is tested on certain sets available in literature and is also applied to pattern recognition and medical diagnosis problems. It is observed that the proposed similarity measure provides a very intuitive quantification.

关键词： Fuzzy sets (FSs) Intuitionistic fuzzy sets (IFSs) Most intuitionistic fuzzy sets (MIFSs) Simi- larity measure (SM) Transformed triangular fuzzy numbers (TTFNs)

Research advances on how metformin improves memory impairment in “chemobrain”

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Neural Regeneration Research 2022年第1期17卷 15-19页

作者： Ahmad Alhowail sridevi Chigurupati Department of Pharmacology and Toxicology College of PharmacyQassim UniversityBuraidahKingdom of Saudi Arabia Department of Medicinal Chemistry and Pharmacognosy College of PharmacyQassim UniversityBuraydahKingdom of Saudi Arabia

Cognitive impairment caused by chemotherapy,referred to as“chemobrain,”is observed in approximately 70% of cancer ***,it is not completely understood how chemotherapy induces cognitive dysfunction,and clinical treatment strategies for this problem are ***,used as a first-line treatment for type 2 diabetes mellitus,is reported to reduce the effects of ***,several studies have examined the effect of metformin in rescuing *** review discusses recent clinical/preclinical studies that addressed some mechanisms of chemobrain and evaluates the effect of metformin in rescuing chemobrain and its potential mechanisms of action.

关键词： behavioral task chemobrain chemotherapy cognitive impairments inflammation memory impairment metformin neuroprotective agent review

Complexes and complexities: INO80 takes center stage

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Molecular Plant 2021年第11期14卷 1776-1778页

作者： sridevi Sureshkumar Sureshkumar Balasubramanian School of Biological Sciences Monash UniversityVIC 3800Australia

Chromatin remodeling and transcriptional reprogramming are key mechanisms through which plants respond to environmental *** dynamics associated with the pres-ence/absence(incorporation/eviction)of the histone variant H2A.Z is one of the key chromatin remodeling mechanisms associated with environmental response(Coleman-Derr and Zilberman,2012).Very recently,some excellent papers(Shang et al.,2021;Willige et al.,2021;Xue et al.,2021)have addressed the role of a less-explored component of this chromatin remodeling-the INO80 ***,we discuss novel insights revealed in these papers and their potential impacts.

关键词： complex. programming insight

Comparative Study of Statistical Features to Detect the Target Event During Disaster

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Big Data Mining and Analytics 2020年第2期3卷 121-130页

作者： Madichetty Sreenivasulu M.sridevi Department of CSE National Institute of TechnologyTiruchirappalliTamilnadu 620015India.

Microblogs,such as facebook and twitter,have much attention among the users and ***,twitter is more popular because of its real-time *** often interacted with real-time events such as earthquakes and floods through *** a disaster,the number of posts or tweets is drastically increased in *** the time of the disaster,detecting a target event is a challenging *** this paper,a framework is proposed for observing the tweets and to detect the target *** detecting the target event,a classifier is devised based on different combinations of statistical features such as the position of the keyword in a tweet,length of a tweet,the frequency of hashtag,and frequency of user mentions and the *** the result,it is evident that the combination of frequency of hashtag and position of keyword features provides good classification results than the other combinations of ***,usage of two features,namely,frequency of hashtag and position of the earthquake keyword reduces the event’s detection *** also these two features are further helpful for detecting the sub-events which are used for filtering the tweets related to the ***,different classifiers such as Artificial Neural Networks(ANN),decision tree,and K-Nearest Neighbor(KNN)are compared by using these two ***,Support Vector Machine(SVM)with linear kernel by using the combination of position of earthquake keyword and frequency of hashtag outperforms state-of-the-art ***,SVM(linear kernel)with proposed features is applied for detecting the earthquake during *** proposed algorithm is tested on Nepal earthquake and landslide datasets,2015.

关键词： disaster twitter Support Vector Machine(SVM) statical features

Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

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Intelligent Automation & Soft Computing 2023年第4期36卷 223-233页

作者： S.sridevi Jeevaa Katiravan Department of Computer Science and Engineering Velammal Engineering CollegeChennai600066India

Scientiﬁc workﬂows have gained the emerging attention in sophisti-cated large-scale scientiﬁc problem-solving *** pay-per-use model of cloud,its scalability and dynamic deployment enables it suited for executing scientiﬁc workﬂow *** the cloud is not a utopian environment,failures are inevitable that may result in experiencingﬂuctuations in the delivered *** a single task failure occurs in workﬂow based applications,due to its task dependency nature,the reliability of the overall system will be affected *** rather than reactive fault-tolerant approaches,proactive measures are vital in scientiﬁc workﬂ*** work puts forth an attempt to con-centrate on the exploration issue of structuring a nature inspired metaheuristics-Intelligent Water Drops Algorithm(IWDA)combined with an efﬁcient machine learning approach-Support Vector Regression(SVR)for task failure prognostica-tion which facilitates proactive fault-tolerance in the scheduling of scientiﬁc workﬂow *** failure prediction models in this study have been implemented through SVR-based machine learning approaches and the precision accuracy of prediction is optimized by IWDA and several performance metrics were evaluated on various benchmark workﬂ*** experimental results prove that the proposed proactive fault-tolerant approach performs better compared with the other existing techniques.

关键词： Failure prediction intelligent water drops support vector regression proactive fault-tolerance scientiﬁc workﬂows precision accuracy resource provisioning

Unveiling the shadows: a qualitative exploration of barriers to rooftop solar photovoltaic adoption in residential sectors

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Clean Energy 2024年第5期8卷 218-228页

作者： Tony C.Mathew sridevi Nagaraja Pandian School of Commerce Kumaraguru College of Liberal Arts and ScienceCoimbatore 641035Tamil NaduIndia

In the face of global climate change,the urgent shift towards renewable energy sources such as solar power is vital for reducing greenhouse gas emissions and fostering a sustainable future,presenting a universal challenge and opportunity for energy policy ***’s adoption of rooftop solar photovoltaic is pivotal due to its vast solar potential,which aligns with national goals to increase renewable energy capacity,reduce carbon emissions,and achieve energy ***’s geographical location offers abundant solar potential,making it a prime candidate for the adoption of rooftop solar photovoltaic *** with the state’s strong commitment to renewable energy initiatives such as the ambitious“SOURA”(solar subsidy program by the Kerala State Electricity Board)project and various incentives for solar adoption,Kerala stands at the forefront of India’s transition towards sustainable energy *** the barriers to rooftop solar photovoltaic adoption in Kerala is crucial for tailoring ef-fective policies and strategies that address specific hindrances from economic constraints to informational *** study employs a qualitative research method to identify the barriers to rooftop solar photovoltaic adoption among households in *** face-to-face interviews with a purposively selected sample of 52 households,the research aims to gain in-depth insights into the multifaceted challenges hindering the widespread adoption of solar energy in residential *** findings reveal several key barriers:financial barriers,informational barriers,technical barriers,regulatory barriers,social barriers,and psychological *** analysis indicates that while there is a predominantly positive attitude towards solar photovoltaic adoption,there are sig-nificant concerns that still need to be *** these barriers with targeted policy interventions and public awareness campaigns could significantly enhance the adoptio

关键词： rooftop solar photovoltaic adoption barriers to solar energy residential solar systems Kerala solar initiatives qualitative analysis in renewable energy

Optimised hybrid classification approach for rice leaf disease prediction with proposed texture features

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Journal of Control and Decision 2024年第1期11卷 84-97页

作者： Sakhamuri sridevi K.Kiran Kumar Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramIndia

This paper aims to frame a new rice disease prediction model that included three major ***,median filtering(MF)is deployed during pre-processing and then‘proposed Fuzzy Means Clustering(FCM)based segmentation’is *** that,‘Discrete Wavelet Transform(DWT),Scale-Invariant Feature Transform(SIFT)and low-level features(colour and shape),Proposed local Binary Pattern(LBP)based features’are extracted that are classified via‘MultiLayer Perceptron(MLP)and Long Short Term Memory(LSTM)’and predicted outcomes are *** exact prediction,this work intends to optimise the weights of LSTM using Inertia Weighted Salp Swarm Optimisation(IW-SSO)***,the development of IW-SSO method is established on varied metrics.

关键词： Rice disease improved fuzzy hybrid classifiers optimised LSTM IW-SSO algorithm

Herbicide resistance: Development of wheat production systems and current status of resistant weeds in wheat cropping systems

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The Crop Journal 2019年第6期7卷 750-760页

作者： sridevi Nakka Mithila Jugulam Dallas Peterson Mohammad Asif Heartland Plant Innovations ManhattanKS 66506USA Department of Agronomy Kansas State University2004 Throckmorton Plant Sciences CenterManhattanKS 66506USA

Herbicide resistance in crops has extended the scope of herbicide applications to control weeds. The introduction of herbicide resistant crops resulted in a major shift in the way that herbicides are used in many crops, but not necessarily increased the prevalence of herbicide use, especially in wheat. Wheat is one of the most widely grown crops in the world and currently only two major herbicide-resistant wheat groups have been commercialized to manage weeds in a cost-effective manner. However, sustainable wheat production is threatened by the expanding occurrence of herbicide-resistant weed populations with limited efforts to discover new herbicide molecules. Selective control of certain problematic weeds in wheat was impossible until development and introduction of the technologies, Clearfield and Co AXium Production Systems. However, the current limitations of reliance on specific herbicides and evolution of resistant weeds mandate precautions and considerations when using these systems to prevent the loss of existing herbicide resources and continue sustainable wheat production. The focus of this review is to provide an overview of natural pre-existing herbicide resistance and development of herbicide-resistant technologies in wheat. The mechanisms of resistance to herbicides in wheat as well as the weed populations in wheat cropping systems, and implications for weed management are discussed.

关键词： Clearfield Coaxium Cytochrome P450s GSTs Herbicide resistance Wheat production systems

Securing Privacy Using Optimization and Statistical Models in Cognitive Radio Networks

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Computer Systems Science & Engineering 2022年第8期42卷 523-533页

作者： R.Neelaveni B.sridevi J.Sivasankari Department of Electronics and Communication Engineering MNM Jain Engineering CollegeChennai60009India Department of Electronics and Communication Engineering Velammal Institute of TechnologyChennai602001India Department of Electronics and Communication Engineering Ultra College of Engineering and TechnologyMadurai625104India

Cognitive Radio Networks(CRN)are the possible and ideal solution for meeting the spectrum needs of next-generation communication *** is a promising alternative approach that allows spectrum sharing in many *** licensed users considered Primary Users(PU)and unlicensed users as Secondary Users(SU).Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service(QoS).Irrespective of using different optimization techniques,the same methodology is to be updated for the *** that,learning and optimization go hand in *** ensures the security in CRN,risk factors in spectrum sharing to SU for secure *** objective of the proposed work is to preserve the location of the SU from attackers and attain the clustering of SU to utilize the *** Colony Optimization(ACO)is implemented to increase the overall efficiency and utilization of the *** is used to form clusters of SUs in the co-operative spectrum sensing *** paper deals with threat detection and classifying threats using parameters such as unlikability,context privacy,anonymity,conditional traceability,and *** this privacy-preserving model,overall accuracy is 97.4%,and it is 9%higher than the conventional models without Privacy-Preserving Architecture(PPA).

关键词： Attacks secondary users cognitive radio networks security