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An Efficient Unsupervised Learning Approach for Detecting Anomaly in Cloud

Computer systems science & Engineering 2023年第4期45卷 149-166页

作者： P.sherubha s.P.sasirekha A.Dinesh Kumar Anguraj J.Vakula Rani Raju Anitha s.phani praveen R.Hariharan Krishnan Department of Information Technology Karpagam College of EngineeringCoimbatoreTamilnaduIndia Department of Computer science and Engineering Karpagam Academy of Higher EducationCoimbatoreTamilnaduIndia Department of Computer science and Engineering Koneru Lakshmaiah Education FoundationAndhra PradeshIndia Department of MCA CMR Institute of TechnologyBengaluruKarnatakaIndia Department of Computer science and Engineering Prasad V.Potluri Siddhartha Institute of TechnologyAndhra PradeshIndia Department of Computer science and Engineering Residency CollegeChennaiIndia

The Cloud system shows its growing functionalities in various industrial *** safety towards data transfer seems to be a threat where Network Intrusion Detection system(NIDs)is measured as an essential element to fulfill ***,Machine Learning(ML)approaches have been used for the construction of intellectual *** IDs are based on ML techniques either as unsupervised or *** supervised learning,NIDs is based on labeled data where it reduces the efficiency of the reduced model to identify attack ***,the unsupervised model fails to provide a satisfactory ***,to boost the functionality of unsupervised learning,an effectual auto-encoder is applied for feature selection to select good ***,the Naïve Bayes classifier is used for classification *** approach exposes the finest generalization ability to train the *** unlabelled data is also used for adoption towards data ***,redundant and noisy samples over the dataset are *** validate the robustness and efficiency of NIDs,the anticipated model is tested over the NsL-KDD *** experimental outcomes demonstrate that the anticipated approach attains superior accuracy with 93%,which is higher compared to J48,AB tree,Random Forest(RF),Regression Tree(RT),Multi-Layer Perceptrons(MLP),support Vector Machine(sVM),and ***,False Alarm Rate(FAR)and True Positive Rate(TPR)of Naive Bayes(NB)is 0.3 and 0.99,*** compared to prevailing techniques,the anticipated approach also delivers promising outcomes.

关键词： Network intrusion detection system feature selection auto-encoder support vector machine(sVM) anomaly

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A study on Outlier Detection and Feature Engineering strategies in Machine Learning for Heart Disease Prediction

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Computer systems science & Engineering 2024年第5期48卷 1085-1112页

作者： Varada Rajkumar Kukkala surapaneni phani praveen Naga satya Koti Mani Kumar Tirumanadham Parvathaneni Naga srinivasu Department of Computer science&Engineering(AIML) MLR Institute of TechnologyHyderabad500043India Department of Computer science and Engineering Prasad V.Potluri Siddhartha Institute of TechnologyVijayawada520007India Department of Computer science&Engineering Sir C.R.Reddy College of EngineeringEluru534001India Amrita school of Computing Amrita Vishwa VidyapeethamAmaravati522503India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil

This paper investigates the application ofmachine learning to develop a response model to cardiovascular problems and the use of AdaBoost which incorporates an application of Outlier Detection methodologies namely;Z-score incorporated with GreyWolf Optimization(GWO)as well as Interquartile Range(IQR)coupled with Ant Colony Optimization(ACO).Using a performance index,it is shown that when compared with the Z-score and GWO with AdaBoost,the IQR and ACO,with AdaBoost are not very accurate(89.0%vs.86.0%)and less discriminative(Area Under the Curve(AUC)score of 93.0%vs.91.0%).The Z-score and GWO methods also outperformed the others in terms of precision,scoring 89.0%;and the recall was also found to be satisfactory,scoring 90.0%.Thus,the paper helps to reveal various specific benefits and drawbacks associated with different outlier detection and feature selection techniques,which can be important to consider in further improving various aspects of diagnostics in cardiovascular ***,these findings can enhance the knowledge of heart disease prediction and patient treatment using enhanced and innovativemachine learning(ML)*** findings when combined improve patient therapy knowledge and cardiac disease prediction through the use of cutting-edge and improved machine learning *** work lays the groundwork for more precise diagnosis models by highlighting the benefits of combining multiple optimization *** studies should focus on maximizing patient outcomes and model efficacy through research on these combinations.

关键词： Grey wolf optimization ant colony optimization Z-score interquartile range(IQR) AdaBoost outlier

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A Novel Multi-objective Protection Coordination scheme for a Microgrid with Optimal Deployment of Dual-setting ROCOV Based Relays

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Protection and Control of Modern Power systems 2024年第4期9卷 23-38页

作者： praveen Kumar Gupta Priyanshul Niranjan Niraj Kumar Choudhary Nitin singh Ravindra Kumar singh the Department of Electrical Engineering Motilal Nehru National Institute of Technology AllahabadPrayagraj 211004India

Relay coordination is crucial in electrical power systems to protect against malfunctions and damage caused by unexpected events like short *** address the challenge associated with the reverse direction of fault current,dual-setting(Ds)directional over-current relays have evolved but failed to provide proper coordination during changes of load,generation,and *** the meantime,with the increasing number of Ds relays,the total relay operating time tends to ***,this paper proposes a protection scheme based on the optimal deployment of conventional and dual-setting rate of change of voltage(Ds-ROCOV)relays in distribution *** holds true for varying network topologies and is unaffected by variations in load and *** objective of the proposed scheme is to ensure reliable and efficient protection against faults in distribution systems by minimizing the overall operating time with the optimal number of Ds-ROCOV *** proposed protection scheme’s performance is evaluated for different coordination time interval values as well as in different microgrid *** paper outlines the design and implementation of the proposed protection scheme which is validated on the modified IEEE 14-bus system using simulations in Matlab/simulink.

关键词： Coordination time interval Ds-ROCOV relay multi-objective optimization optimal-deployment protection coordination

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Improving hydrogen evolution reaction efficiency through lattice tuning

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Nano Research 2024年第7期17卷 5907-5913页

作者： Zipeng Zhao Haotian Liu Wenpei Gao praveen Kolla Wang Xue Zeyan Liu Jinghua Guo sanjeev Mukerjee Xiaoqing Pan Qingying Jia Xiangfeng Duan Yu Huang Department of Materials science and Engineering University of CaliforniaLos AngelesCalifornia 90095USA Department of Chemical Engineering and Materials science University of CaliforniaIrvineCalifornia 92697USA Materials science and Engineering North Carolina State UniversityRaleighNorth Carolina 27695USA Department of Chemistry and Chemical Biology Northeastern UniversityBostonMassachusetts 02115USA Department of Chemistry and Biochemistry University of CaliforniaLos AngelesCalifornia 90095USA Advanced Light source Lawrence Berkeley National LaboratoryBerkeleyCalifornia 94720USA Department of Chemistry and Biochemistry University of CaliforniaSanta CruzCalifornia 95064USA Department of Physics and Astronomy University of CaliforniaIrvineCalifornia 92697USA California Nanosystems Institute University of CaliforniaLos AngelesCalifornia 90095USA

The intermittent nature of renewable energy sources sets a requirement for efficient energy storage to mitigate the conflict between energy supply and *** is a promising choice for energy storage due to its high energy ***,the conversion of electrical energy to chemical energy stored in hydrogen through water electrolysis suffers from low efficiency,and the electricity cost dominates the total cost of hydrogen ***,we report the study of improving the hydrogen evolution reaction activity of Pt-based catalysts by building a nanoscale surface NiO and Pt interface,further optimizing the performance via tuning the lattice parameter of the core of nanoparticles,which can be achieved by varying the dealloying annealing *** optimized PtCuNi-O/C and PtNi-O/C catalysts are demonstrated to be one of the best catalysts,with a mass activity(MA)of 9.1 and 8.7 mA/μgPt,which is 9.9-fold and 9.5-fold of that of Pt/C,respectively.

关键词： lattice tuning Pt-based catalyst hydrogen evolution reaction electrocatalysis

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Deep Learning-Based speech Emotion Recognition: Leveraging Diverse Datasets and Augmentation Techniques for Robust Modeling

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Journal of Harbin Institute of Technology(New series) 2024年

作者： Ayush Porwal praveen Kumar Tyagi Ajay sharma Dheeraj Kumar Agarwal Department of Electronics and Instrumentation Engineering， shri G.s.Institute of Technology and science Department of Electronics and Communication Engineering， Maulana Azad National Institute of Technology school of Computing science and Engineering， VIT Bhopal University

In recent years， speech Emotion Recognition (sER) has developed into an essential instrument for interpreting human emotions from auditory data. The proposed research focused on the development of a sER system employing deep learning and multiple datasets containing samples of emotive speech. The primary objective of this research endeavor is to investigate the utilization of Convolutional Neural Networks (CNNs) in the process of sound feature extraction. stretching， pitch manipulation， and noise injection are a few of the techniques utilized in this study to improve the data quality. The investigation includes coverage of these methods. Feature extraction methods including Zero Crossing Rate， Chroma＿stft， MFCC， RMs， and Melspectogram are used to train a model. By using these techniques， audio signals can be transformed into recognized features that can be utilized to train the model. Ultimately， the study will produce a thorough evaluation of the model’s performance. When this method was applied， the model achieved an impressive accuracy of 94.57% on the test dataset. Proposed work also validated on EMO-BD and IEMOCAP dataset. These consist of further data augmentation， feature engineering， and hyperparameter optimization. By following these development paths， sER systems will be able to be implemented in real-world scenarios with greater accuracy and resilience.

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spin squeezing in Dicke-class of states with non-orthogonal spinors

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Chinese Physics B 2019年第6期28卷 66-71页

作者： K s Akhilesh K s Mallesh sudha praveen G Hegde Department of Physics University of MysoreManasagangotriMysuru-570006KarnatakaIndia Department of Physics Kuvempu UniversityShankaraghattaShimoga-577451India Inspire Institute Inc. AlexandriaVirginia 22303USA

The celebrated Majorana representation is exploited to investigate spin squeezing in different classes of pure symmetric states of N qubits with two distinct spinors, namely the Dicke-class of states. On obtaining a general expression for spin squeezing parameter, the variation of squeezing for different configurations is studied in detail. It is shown that the states in the Dicke-class, characterized by two-distinct non-orthogonal spinors, exhibit squeezing.

关键词： Majorana representation of pure symmetric multiqubit states spin squeezing Dicke states

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Predictors of cerebrospinal fluid GeneXpert MTB/RIF positivity in patients with tuberculous meningitis:A prospective cohort study

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Asian Pacific Journal of Tropical Medicine 2024年第10期17卷 465-472页

作者： Priyanka Gupta Neeraj Kumar Ravindra Kumar Garg Hardeep singh Malhotra Imran Rizvi Rajesh Verma praveen Kumar sharma Ravi Uniyal shweta Pandey Amita Jain Parul Jain Department of Neurology King George’s Medical UniversityLucknowIndia Department of Microbiology King George’s Medical UniversityLucknowIndia

Objective:To identify the clinical,laboratory,and radiological markers that could predict a positive GeneXpert result in patients suspected of tuberculous ***:In this prospective,observational study,patients with tuberculous meningitis were systematically *** clinical,laboratory[including cerebrospinal fluid(CsF)microscopy,culture,and GeneXpert],and neuroimaging factors were *** participants were administered anti-tuberculous treatment and corticosteroids.A six-month follow-up was done to evaluate the ***:Of the 116 patients studied,54(46.6%)tested positive for GeneXpert,while 62(53.4%)were *** cranial nerve involvement(OR 3.71,95%CI 1.052-13.09,P=0.04)and the presence of basal exudates on neuroimaging(OR 5.22,95%CI 2.03-13.42,P=0.001)emerged as independent predictive factors for a positive GeneXpert result.A positive CsF GeneXpert result(P=0.002)and drug resistance(P=0.004)were significantly linked to adverse ***,a high score on the Medical Research Council stageⅢ(OR 5.64,95%CI 1.18-26.87,P=0.03)and elevated CsF cell counts(OR 1.002,95%CI 1.00-1.001,P=0.03)were identified as independent predictors of poor ***:Third cranial nerve involvement and the presence of basal exudates were significant indicators of a positive GeneXpert *** stageⅢdisability and elevated CsF cell counts predicted poor outcomes.

关键词： Tuberculous meningitis Mycobacterium tuberculosis Cerebrospinal fluid Ziehl-Neelsen staining GeneXpert

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Image based leaf segmentation and counting in rosette plants

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Information Processing in Agriculture 2019年第2期6卷 233-246页

作者： J.praveen Kumar s.Domnic National Institute of Technology TiruchirappalliIndia

This paper proposes an efficient method to extract the leaf region and count the number of leaves in digital plant *** plant image analysis plays a significant role in viable and productive *** is used to record the plant growth,plant yield,chlorophyll fluorescence,plant width and tallness,leaf area,*** and *** growth is a major character to be analyzed among these plant characters and it directly depends on the number of leaves in the *** this paper,a new method is presented for leaf region extraction from plant images and counting the number of *** proposed method has three *** first step involves a new statistical based technique for image *** second step involves in the extraction of leaf region in plant image using a graph based *** third step involves in counting the number of leaves in the plant image by applying Circular Hough Transform(CHT).The proposed work has been experimented on benchmark datasets of Leaf segmentation Challenge(LsC).The proposed method achieves the segmentation accuracy of 95.4%and it also achieves the counting accuracy of0.7(DiC)and 2.3(|DiC|)for datasets(A1,A2 and A3),which are better than the state-of-the-art methods.

关键词： Plant image analysis Plant phenotyping Leaf region extraction Leaf count

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Cold dwell behaviour of Ti6Al alloy:Understanding load shedding using digital image correlation and dislocation based crystal plasticity simulations

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Journal of Materials science & Technology 2022年第33期128卷 254-272页

作者： Yi Xiong NicolòGrilli phani s.Karamched Bo-shiuan Li Edmund Tarleton Angus J.Wilkinson Department of Materials University of OxfordParks RoadOxfordOX13PHUnited Kingdom Department of Mechanical Engineering University of BristolQueen’s BuildingUniversity WalkBristolUnited Kingdom Department of Engineering science University of OxfordParks RoadOxfordOX13PJUnited Kingdom

Digital image correlation(DIC)and dislocation based crystal plasticity simulation were utilised to study cold dwell behaviour in a coarse grain Ti-6Al alloy at 3 different temperatures up to 230℃.strains extracted from large volume grains were measured during creep by DIC and were used to calibrate the crystal plasticity *** values of critical resolved shear stresses(CRss)of the two main slip systems(basal and prismatic)were determined as a function of *** along paths across the boundaries of four grain pairs,three“rogue”grain pairs and one“non-rogue”grain pair,were determined at different *** load shedding was observed in one of the“rogue”grain pairs,where a stress increment during the creep period was found in the“hard”grain.A minor load shedding mechanism was observed in two non-typical“rogue”grain pairs,in which the plastic deformation is nonuniform inside the grains and geometrically necessary dislocations accumulate in the centre of the *** elevated temperatures,120℃was found to be the worst case scenario as the stress difference at the grain boundaries of these four grain pairs was found to be the largest among the three temperatures *** origin of this critical temperature is debated in the literature and it is investigated for the first time in the present work by analysing the simultaneous effects of the geometrically necessary dislocations(GND)and the strain rate sensitivity(sRs)of the slip *** analysis shows that the combined effects of the peak sRs of both prismatic and basal slip systems at 80℃and of the increase of the spread of the GND distribution around the grain boundary at higher temperatures are the origin of the observed worst case scenario.

关键词： Cold dwell fatigue Digital image correlation Crystal plasticity Load shedding Titanium alloy

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Effect of glycerol on densification of agricultural biomass

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International Journal of Agricultural and Biological Engineering 2015年第1期8卷 64-73页

作者： shahram Emami Lope G Tabil phani Adapa Department of Plant sciences University of Saskatchewan51 Campus DriveSaskatoonSK S7N 5A8 Canada Department of Chemical and Biological Engineering College of EngineeringUniversity of Saskatchewan57 Campus DriveSaskatoonSK S7N 5A9 Canada Global Institute for Water security University of SaskatchewanNational Hydrology Research Centre11 Innovation BoulevardSaskatoonSK S7N 3H5 Canada

Experiments were conducted to verify the effect of adding glycerol for pelleting of selected agricultural crop residues,namely,wheat,barley,oat and canola *** pelleting tests were conducted to study the effect of biomass type,hammer mill screen size,and crude glycerol content(co-product of biodiesel industry)on pellet quality(density and durability),ash content and gross heat of *** types of biomass were ground at three different hammer mill screen sizes of 6.4,3.2 and 1.6 *** biomass was mixed with three levels of glycerol of 2.5%,5.0%and 7.5% by *** were made at a pre-set load of 4400 N(138.9 MPa)using single-pelleting unit attached to an Instron testing *** of pellets was determined by measuring pellet density,relaxed density,durability(measured by pellet drop test)and specific energy required to make a *** gross heat of combustion and ash content of pellets were also determined and *** highest pellet density(988-1133 kg/m^(3))and relaxed density(992-1142 kg/m^(3))were obtained from biomass ground using a hammer mill screen size of 6.4 mm.A decrease in hammer mill screen size resulted in reduced *** highest durability of biomass obtained from hammer mill screen size of 6.4 mm ranged from 97%-100%.Addition of glycerol resulted in lower ash content in majority of *** highest gross heat of combustion was observed in pellets made from wheat straw with 7.5% glycerol content(38.3 MJ/kg).Addition of glycerol resulted in lower pellet densities,lower ash content,no change in durability and higher gross heating values.

关键词： biomass biofuels glycerol pelleting caloric value heating value

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