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Fuzzy–frequency ratio model for avalanche susceptibility mapping

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International Journal of Digital Earth 2016年第12期9卷 1168-1184页

作者： Satish kumar Snehmani Pankaj kumar Srivastava Akshay Gore Mritunjay kumar Singh College of Engineering Studies University of Petroleum&Energy Studies(UPES)DehradunUttarakhandIndia Snow and Avalanche Study Establishment Defence Research&Development Organisation(DRDO)ChandigarhIndia Spatial Strokes Technologies Private Limited ZirakpurPunjabIndia

Avalanche activities in the Indian Himalaya cause the majority of fatalities and responsible for heavy damage to the *** susceptibility maps assist decision-makers and planners to execute suitable measures to reduce the avalanche *** the present study,a probabilistic data-driven geospatial fuzzy–frequency ratio(fuzzy–FR)model is proposed and developed for avalanche susceptibility mapping,especially for the large undocumented *** fuzzy–FR model for avalanche susceptibility mapping is initially developed and applied for Lahaul-Spiti *** fuzzy–FR model utilized the six avalanche occurrence factors(***,aspect,curvature,elevation,terrain roughness and vegetation cover)and one referent avalanche inventory map to generate the avalanche susceptibility *** 292 documented avalanche locations from the avalanche inventory map,233(80%)were used for training the model and remaining 59(20%)were used for validation of the *** avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve(ROC-AUC)*** validation of the results using ROC-AUC technique,the success rate and prediction rate were *** values of success rate and prediction rate were 94.07%and 91.76%,*** validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping.

关键词： Snow avalanche avalanche susceptibility mapping GIS fuzzy–frequency ratio(fuzzy–FR)model Lahaul&Spiti

Comparative study on machinability improvement in hard turning using coated and uncoated carbide inserts： part II modeling, multi-response optimization, tool life, and economic aspects

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Advances in Manufacturing 2018年第2期6卷 155-175页

作者： Ramanuj kumar Ashok kumar Sahoo Purna Chandra Mishra Rabin kumar Das School of Mechanical Engineering Kalinga Institute of Industrial Technology Bhubaneswar-24 Odisha India

The present study focused on mathematical modeling, multi response optimization, tool life, and eco- nomical analysis in finish hard turning of AISI D2 steel （（55 4- 1） HRC） using CVD-coated carbide （TiN/TiCN/ A1203） and uncoated carbide inserts under dry environ- mental conditions. Regression methodology and the grey relational approach were implemented for modeling and multi-response optimization, respectively. Comparative economic statistics were carried out for both inserts, and the adequacy of the correlation model was verified. The experimental and predicted values for all responses were very close to each other, implying the significance of the model and indicating that the correlation coefficients were close to unity. The optimal parametric combinations for A1203 coated carbide were dl-fl-v2 （depth of cut = 0.1 mm, feed = 0.04 mm/r and cutting speed = 108 m/min）, and those for the uncoated tool were dl-（0.1 mm）-fl （0.04 mm/r）-vl （63 rn/min）. The observed tool life for the coated carbide insert was 15 times higher than that for the uncoated carbide insert, considering flank wear criteria of 0.3 mm. The chip volume after machining for the coated carbide insert was 26.14 times higher than that of the uncoated carbide insert and could be better utilized for higher material removal rate. Abrasion, diffusion, notch- ing, chipping, and built-up edge have been observed to be the principal wear mechanisms for tool life estimation. Use of the coated carbide tool reduced machining costs by about 3.55 times compared to the use of the uncoated carbide insert, and provided economic benefits in hard turning.

关键词： Machinability Hard turning Regression Grey relational analysis Tool life Economic analysis

Non-invasive optical characterization and estimation of Zn porosity in gas tungsten arc welding of Fe–Al joints using CR model and OES measurements

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Plasma Science and Technology 2023年第11期25卷 133-141页

作者： Sai SRIKAR Tinku kumar Degala Venkata KIRAN Reetesh kumar GANGWAR Department of Physics&CAMOST Indian Institute of Technology TirupatiYerpedu 517619India Department of Mechanical Engineering Indian Institute of Technology TirupatiYerpedu 517619India

In this study,we employed a non-invasive approach based on the collisional radiative(CR)model and optical emission spectroscopy(OES)measurements for the characterization of gas tungsten arc welding(GTAW)discharge and quantification of Zn-induced porosity during the GTAW process of Fe–Al *** OES measurements were recorded as a function of weld current,welding speed,and input *** OES measurements revealed significant line emissions from Zn-I in 460–640 nm and Ar-I in 680–800 nm wavelength ranges in all experimental *** OES coupled CR model approach for Zn-I line emission enabled the simultaneous determination of both essential discharge parameters *** temperature and electron ***,these predictions were used to estimate the Zn-induced porosity using OES-actinometry on Zn-I emission lines using Ar as actinometer *** OES-actinometry results were in good agreement with porosity data derived from an independent approach,i.e.x-ray radiography *** current study shows that OES-based techniques can provide an efficient route for real-time monitoring of weld quality and estimate porosity during the GTAW process of dissimilar metal joints.

关键词： optical emission spectroscopy collisional radiative model actinometry GTAW Fe Al joints Zn vapor porosity radiographic imaging(Some figures may appear in colour only in the online journal)

Comparative Analysis of Photo-Crystallization in a-Se95Te5 and a-Se95In5 Alloys

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Chinese Physics Letters 2006年第11期23卷 3061-3064页

作者： N. Mehta D. kumar A. kumar Department of Physics Pranveer Singh Institute of Technology Kanpur India Department of Physics JSS Academy of Technical Education Noida India Department of Physics Harcourt Butler Technological Institute Kanpur India

We report a comparative study on photo-crystallization in a-Se95 Te5 and a-Se95In5 alloys. The photo-crystallization is achieved by a shining white line on the thin films of these alloys in vacuum for different exposure times. The results indicate that photo-crystallization is fast in a-Se95In5 alloy as compared to a-Se95 Te5 alloy. This is explained in terms of lower thermal stability of a-Se95In5 alloy as compared to a-Se95 Te5 alloy.

关键词： AMORPHOUS THIN-FILMS CHALCOGENIDE GLASSES TRANSIENT PHOTOCONDUCTIVITY STEADY-STATE SELENIUM KINETICS PHOTOCRYSTALLIZATION TRANSITION SEMICONDUCTORS SE100-XINX

Comparative investigation towards machinability improvement in hard turning using coated and uncoated carbide inserts： part Iexperimental investigation

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Advances in Manufacturing 2018年第1期6卷 52-70页

作者： Ramanuj kumar Ashok kumar Sahoo Purna Chandra Mishra Rabin kumar Das School of Mechanical Engineering Kalinga Institute of Industrial Technology BhubaneswarOdisha 751024 India

The investigation of low cost uncoated andcoated carbide insert in the hard turning of hardened AISID2 steel （≥55 HRC） will definitely open up a new arena asan economical alternative suitable to industrial machiningsectors. Thus, this paper reports the comparative machin-ability assessment for the hard turning of AISI D2 steel（（55 ± 1） HRC） by coated and uncoated carbide insert in adry environment. Micro hardness and abrasion tests werecarried out to assess resistance capability against wear. Theabove test results confirmed the greater wear resistanceability of AIaO3 coated carbide insert over uncoated car-bide. Based on the extensive investigation of comparativemachinability, the coated carbide insert （TiN-TiCN-A12O3）outperformed the uncoated carbide insert with regard tosurface roughness, flank wear, chip-tool interface temper-ature, and chip morphology. Abrasion and diffusion wereobserved as the principal tool wear mechanisms in theinvestigated range. The uncoated carbide failed completelydue to the severe chipping and quick dulling of the cuttingedge, which led to its unsuitability for machining hardenedsteel.

关键词： Coated and uncoated carbide Hard turning Machinability Flank wear Surface roughness Chipmorphology Cutting temperature

Stator Fault Diagnosis of Induction Motor Based on Discrete Wavelet Analysis and Neural Network Technique

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Chinese Journal of Electrical Engineering 2023年第1期9卷 142-157页

作者： Abdelelah Almounajjed Ashwin kumar Sahoo Mani Kant kumar Sanjeet kumar Subudhi Electrical Engineering Department C.V Raman Global UniversityBhubaneswar 752054India Electronics and Communication Engineering Department C.V Raman Global UniversityBhubaneswar 752054India

A novel approach by introducing a statistical parameter to estimate the severity of incipient stator inter-turn short circuit(ITSC)faults in induction motors(IMs)is *** the incipient ITSC fault and its severity is challenging for several *** stator currents in the healthy and faulty cases are highly similar during the primary stage of the ***,the conventional statistical parameters resulting from the analysis of fault signals do not consistently show a systematic variation with respect to the increase in fault *** objective of this study is the early detection of incipient ITSC ***,it aims to determine the percentage of shorted turns in the faulty phase,which acts as an indicator for severe damage to the stator *** of the motor in healthy and defective cases is performed using the Clarke Concordia transform.A discrete wavelet transform is applied to the motor currents using a Daubechies-8 *** statistical parameters L1 and L2 norms are computed for the detailed *** parameters are obtained under a variety of loads and defects to acquire the most accurate and generalized features related to the *** L1 and L2 norms creates a novel statistical parameter with notable characteristics to achieve the research *** artificial neural network-based back propagation algorithm is employed as a classifier to implement the classification *** classifier output defines the percentage of defective turns with a high level of *** competency of the adopted methodology is validated via simulations and *** results confirm the merits of the proposed method,with a classification test correctness of 95.29%.

关键词： Discrete wavelet transform induction motor inter-turn short circuit fault neural networks statistical parameters

Melanoma Detection Based on Hybridization of Extended Feature Space

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Intelligent Automation & Soft Computing 2023年第8期37卷 2175-2198页

作者： Anuj kumar Shakti kumar DCSA Panjab UniversityChandigarh160014India

Melanoma is a perfidious form of skin *** study offers a hybrid framework for the automatic classification of *** Auto-matic Melanoma Detection System(AMDS)is used for identifying melanoma from the infected area of the skin image using image processing techniques.A larger number of pre-existing automatic melanoma detection systems are either commercial or their accuracy can be further *** research problem is to identify the best preprocessing technique,feature extractor,and classifier for melanoma detection using publically available MED-NODE data *** goes through four *** preprocessing stage is for noise removal;the segmentation stage is for extracting lesions from infected skin images;the feature extraction stage is for determining the features like asymmetry,border,and color,and the classification stage is to classify the lesion as benign or *** infected input image for the AMDS may contain impurities such as noise,illumination,artifacts,and *** the proposed methodology an algorithm LePrePro is proposed for the prepro-cessing stage for denoising and brightness cum contrast normalization and another algorithm LeFET is proposed for extending the feature vector space in the feature extraction stage using a hybrid *** the study,a novel approach has been proposed in which different classifiers,feature extractions,and data preprocessing steps of the AMDS are *** a conclusion,this comparison revealed that on experimentation using Med-Node and ISIC 2017 Dataset,the best results included Gaussian blur as the best data preprocessing step,Extended feature vector which is the combination of Hue Saturation Value(HSV),and Local Binary Pattern(LBP)was the best feature extraction method,and the ensemble bagged tree was the best classification technique on the Med-Node data sets with 99%Area Under the Receiver Operating Characteristic Curve(AUC),93.52%accuracy,90.82%sensitivity,and 98.36%specificity in the proposed

关键词： Machine learning melanoma detection feature extraction benign classification image processing

Cosmological Constant Dominated Transit Universe from the Early Deceleration Phase to the Current Acceleration Phase in Bianchi-V Spacetime

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Chinese Physics Letters 2012年第7期29卷 298-302页

作者： YADAV Anil kumar Department of Physics Anand Engineering CollegeKeethamAgra-282007India

We present the transition of the universe from the early decelerating phase to the current accelerating phase with viscous fluid and time-dependent cosmological constant (A) as a source of matter in Bianchi- V *** study the transit behaviour of the universe,we assume the scale factor as an increasing function of time,which generates a time-dependent deceleration parameter (DP).The study revesls that the cosmological term does not change its fundamental nature for ε =const and ε =ε(t),where ε is the coefficient of bulk *** A(t)is found to be positive and is a decreasing function of *** same behavior was observed during recent supernovae *** physical behaviour of the universe is discussed in detail.

关键词： universe behaviour Phase

A Clinical Data Analysis Based Diagnostic Systems for Heart Disease Prediction Using Ensemble Method

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Big Data Mining and Analytics 2023年第4期6卷 513-525页

作者： Ankit kumar Kamred Udham Singh Manish kumar Department of Computer Engineering and Applications GLA UniversityMathura 281406India School of Computing Graphic Era Hill UniversityDehradun 248002India Department of Electronics and Communication Engineering GLA UniversityMathura 281406India.

The correct diagnosis of heart disease can save lives,while the incorrect diagnosis can be *** UCI machine learning heart disease dataset compares the results and analyses of various machine learning approaches,including deep *** used a dataset with 13 primary characteristics to carry out the *** vector machine and logistic regression algorithms are used to process the datasets,and the latter displays the highest accuracy in predicting coronary *** programming is used to process the *** research initiatives have used machine learning to speed up the healthcare *** also used conventional machine learning approaches in our investigation to uncover the links between the numerous features available in the dataset and then used them effectively in anticipation of heart infection *** the accuracy and confusion matrix has resulted in some favorable *** get the best results,the dataset contains certain unnecessary features that are dealt with using isolation logistic regression and Support Vector Machine(SVM)classification.

关键词： artificial intelligence support vector machine logistic regression cleveland dataset supervised algorithm human sensing