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Natural Resources 2010年第1期1卷 11-18页

作者： manish kumar goyal Chandra Shekhar Prasad Ojha 不详

In this paper, downscaling models are developed using various linear regression approaches namely direct, forward, backward and stepwise regression for downscaling of GCM output to predict mean monthly precipitation under IPCC SRES scenarios to watershed-basin scale in an arid region in India. The effectiveness of these regression approaches is evaluated through application to downscale the predictand for the Pichola lake region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1948–2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001–2100. The selection of important predictor variables becomes a crucial issue for developing downscaling models since reanalysis data are based on wide range of meteorological measurements and observations. Direct regression was found to yield better performance among all other regression techniques explored in the present study. The results of downscaling models using both approaches show that precipitation is likely to increase in future for A1B, A2 and B1 scenarios, whereas no trend is discerned with the COMMIT.

关键词： Backward Forward Precipitation Regression Stepwise

Application of PLS-Regression as Downscaling Tool for Pichola Lake Basin in India

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International Journal of Geosciences 2010年第2期1卷 51-57页

作者： manish kumar goyal Chandra Shekhar Prasad Ojha 不详

In this paper, downscaling models are developed using Partial Least Squares (PLS) Regression for obtaining projections of mean monthly precipitation to lake-basin scale in an arid region in India. The effectiveness of this approach is demonstrated through application to downscale the predictand for the Pichola lake region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1948-2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001-2100. The selection of important predictor variables becomes a crucial issue for developing downscaling models since reanalysis data are based on wide range of meteorological measurements and observations. In this paper, we use PLS regression for quality prediction and its use for the variable selection based on the variable importance. The results of downscaling models using PLS regression show that precipitation is projected to increase in future for A2 and A1B scenarios, whereas it is least for B1 and COMMIT scenarios using predictors.

关键词： PLS Regression Precipitation VIP Score

Analysis of Mean Monthly Rainfall Runoff Data of Indian Catchments Using Dimensionless Variables by Neural Network

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Journal of Environmental Protection 2010年第2期1卷 155-171页

作者： manish kumar goyal Chandra Shekhar Prasad Ojha 不详

This paper focuses on a concept of using dimensionless variables as input and output to Artificial Neural Network (ANN) and discusses the improvement in the results in terms of various performance criteria as well as simplification of ANN structure for modeling rainfall-runoff process in certain Indian catchments. In the present work, runoff is taken as the response (output) variable while rainfall, slope, area of catchment and forest cover are taken as input parameters. The data used in this study are taken from six drainage basins in the Indian provinces of Madhya Pradesh, Bihar, Rajasthan, West Bengal and Tamil Nadu, located in the different hydro-climatic zones. A standard statistical performance evaluation measures such as root mean square (RMSE), Nash–Sutcliffe efficiency and Correlation coefficient were employed to evaluate the performances of various models developed. The results obtained in this study indicate that ANN model using dimensionless variables were able to provide a better representation of rainfall–runoff process in comparison with the ANN models using process variables investigated in this study.

关键词： Dimensional Variables Artificial Neural Networks Rainfall–Runoff

Can Emax and platelet count truly differentiate between benign and malignant liver lesions?

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World Journal of Gastroenterology 2025年第3期31卷 120-122页

作者： Manjeet kumar goyal Omesh goyal Department of Gastroenterology and Human Nutrition Unit All India Institute of Medical SciencesNew Delhi 110029DelhiIndia Department of Gastroenterology Dayanand Medical College and HospitalLudhiana 141001PunjabIndia

This letter critically evaluates Jiang et al's article on the differentiation of benign and malignant liver lesions using Emax and platelet *** notable findings,significant methodological and interpretative limitations are *** study lacks detailed assay conditions for Emax measurement,employs inadequate statistical methods without robust multivariate analysis,and does not provide clinically relevant threshold *** nomogram's reliance on Emax as a major diagnostic contributor is questionable due to attenuation in hepatocellular carcinoma patients with ***,the study's limitations,such as selection bias and confounding factors,are not adequately *** research should adopt more rigorous methodologies,including prospective studies with larger cohorts and standardized protocols for biomarker measurement,to enhance validity and clinical applicability.

关键词： Emax Platelet count Benign liver lesions Malignant liver lesions Hepatocellular carcinoma Cirrhosis Diagnostic biomarkers Shear wave elastography Methodological limitations Clinical utility

Species richness,phylogenetic diversity and phylogenetic structure patterns of exotic and native plants along an elevational gradient in the Himalaya

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Ecological Processes 2021年第1期10卷 877-889页

作者： kumar manish Department of Environmental Studies Dr.Bhim Rao Ambedkar CollegeUniversity of DelhiDelhiIndia

Background:So far,macroecological studies in the Himalaya have mostly concentrated on spatial variation of overall species richness along the elevational *** few studies have attempted to document the diference in elevational richness patterns of native and exotic *** this study,this knowledge gap is addressed by integrating data on phylogeny and elevational distribution of species to identify the variation in species richness,phylogenetic diversity and phylogenetic structure of exotic and native plant species along an elevational gradient in the ***:Species distribution patterns for exotic and native species difered;exotics tended to show maximum species richness at low elevations while natives tended to predominate at *** species assemblages showed higher phylogenetic diversity than the exotic species assemblages over the entire elevational gradient in the *** terms of phylogenetic structure,exotic species assemblages showed majorly phylogenetic clustering while native species assemblages were characterized by phylogenetic overdispersion over the entire ***:The fndings of this study indicate that areas with high native species richness and phylogenetic diversity are less receptive to exotic species and vice versa in the *** assemblages with high native phylogenetic overdispersion are less receptive to exotic species than the phylogenetically clustered *** ecological processes(ecological fltering in case of exotics and resource and niche competition in case of natives)may govern the distribution of exotic and native species along the elevational gradient in the Himalaya.

关键词： Exotic species Native species Himalaya Elevational gradient Richness pattern

An efficient hybrid computational technique for the time dependent Lane-Emden equation of arbitrary order

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Journal of Ocean Engineering and Science 2022年第2期7卷 131-142页

作者： manish goyal Amit Prakash Dumitru Baleanu Department of Mathematics Institute of Applied Sciences and HumanitiesGLA UniversityMathuraIndia Department of Mathematics National Institute of TechnologyKurukshetraIndia Department of Mathematics Faculty of Arts and SciencesCankaya UniversityEtimesgutTurkey Institute of Space Sciences Magurele-BucharestRomania

The study of dynamic behaviour of nonlinear models that arise in ocean engineering play a vital role in our daily *** are many examples of ocean water waves which are nonlinear in *** shallow water,the linearization of the equations imposes severe conditions on wave amplitude than it does in deep water,and the strong nonlinear effects are *** this paper,q-homotopy analysis Laplace transform scheme is used to inspect time dependent nonlinear Lane-Emden type equation of arbitrary *** offers the solution in a fast converging *** uniqueness and convergence analysis of the considered model is *** given examples confirm the competency as well as accuracy of the presented *** behavior of obtained solution for distinct orders of fractional derivative is dis-cussed through *** auxiliary parameter¯h offers a suitable mode of handling the region of *** outcomes reveal that the q-HATM is attractive,reliable,efficient and very effective.

关键词： Fractional differential equations(FDE) Time dependent Lane-Emden type differential equation Caputo derivative of arbitrary order q-homotopy analysis transform scheme(q-HATM) Laplace transform

A Novel Approach for Enhancement of Geometric and Contrast Resolution Properties of Low Contrast Images

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 628-638页

作者： Koushlendra kumar Singh manish kumar Bajpai Rajesh kumar Pandey Department of Computer Science and Engineering National Institute of Technology Jamshedpur 831014 India Indian Institute of Information Technology Design & Manufacturing Jabalpur MP 482005 India Department of Mathematical Sciences In- dian Institute of Technology Varanasi U.P. 221005 India

The present work encompasses a new image enhancement algorithm using newly constructed Chebyshev fractional order differentiator. We have used Chebyshev polynomials to design Chebyshev fractional order differentiator. We have generated the high pass filter corresponding to it. The designed filters are applied for decomposing the input image into four bands and low-low(L-L) sub-band is updated using correction coefficients. Reconstructed image with updated L-L sub-band provides the enhanced image. The visual results obtained are encouraging for image enhancement. The applicability of the developed algorithm is illustrated on three different test *** effects of order of differentiation on the edges of images have also been presented and discussed.

关键词： Index Terms-Chebyshev polynomial based approximation contrast enhancement fractional order differentiator.

Machine Learning-based Electric Load Forecasting for Peak Demand Control in Smart Grid

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Computers, Materials & Continua 2023年第3期74卷 4785-4799页

作者： manish kumar Nitai Pal Department of Electrical Engineering Indian Institute of Technology(ISM)Dhanbad826004India Department of Nuclear Science&Technology Pandit Deendayal Energy UniversityGandhinagarIndia

Increasing energy demands due to factors such as population,globalization,and industrialization has led to increased challenges for existing energy *** ways of energy generation and energy consumption like smart grids and smart homes are implemented to face these challenges with reliable,cheap,and easily available sources of *** integration of renewable energy and other clean distributed generation is increasing continuously to reduce carbon and other air pollutants *** the integration of distributed energy sources and increase in electric demand enhance instability in the ***-term electrical load forecasting reduces the grid fluctuation and enhances the robustness and power quality of the *** load forecasting in advance on the basic historical data modelling plays a crucial role in peak electrical demand control,reinforcement of the grid demand,and generation balancing with cost *** accurate forecasting of electrical data is a very challenging task due to the nonstationary and nonlinearly nature of the *** learning and artificial intelligence have recognized more accurate and reliable load forecastingmethods based on historical load *** purpose of this study is to model the electrical load of Jajpur,Orissa Grid for forecasting of load using regression type machine learning algorithms Gaussian process regression(GPR).The historical electrical data and whether data of Jajpur is taken for modelling and simulation and the data is decided in such a way that the model will be considered to learn the connection among past,current,and future dependent variables,factors,and the relationship among *** on this modelling of data the network will be able to forecast the peak load of the electric grid one day *** study is very helpful in grid stability and peak load control management.

关键词： Artificial intelligence electric load forecasting machine learning peak-load control renewable energy smart grids

Critical analysis of the effects of proton pump inhibitors on inflammatory bowel disease:An updated review

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World Journal of Gastroenterology 2024年第37期30卷 4160-4162页

作者： Omesh goyal Manjeet kumar goyal Department of Gastroenterology Dayanand Medical College and HospitalLudhiana 141001PunjabIndia Department of Gastroenterology and Human Nutrition All India Institute of Medical SciencesNew Delhi 110029DelhiIndia

This letter critically evaluates the effects of proton pump inhibitors(PPIs)on inflammatory bowel disease,particularly focusing on Crohn's disease(CD)and ulcerative colitis(UC),as discussed in Liang et al’s recent *** the review provides significant insights,it relies heavily on cross-sectional and observational studies,which limits the ability to draw causal *** heterogeneous study populations and inconsistent definitions of long-term PPI use further complicate the *** letter also highlights the need for rigorous control of confounding factors and considers the potential publication bias in the existing *** implications of these issues are discussed in the context of both CD and UC,and future research directions are proposed to address these shortcomings.

关键词： Proton pump inhibitors Inflammatory bowel disease Gut microbiota Intestinal mucosal barrier Immune cell function

Emergence of blockchain-technology application in peer-to-peer electrical-energy trading: a review

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Clean Energy 2021年第1期5卷 104-123页

作者： manish kumar Thukral Manipal University Jaipur Electrical Engineering DepartmentJaipurIndia

Renewable-energy resources require overwhelming adoption by the common masses for safeguarding the environment from *** this context,the prosumer is an important emerging concept.A prosumer in simple terms is the one who consumes as well as produces electricity and sells it either to the grid or to a *** the present scenario,peer-to-peer(P2P)energy trading is gaining momentum as a new vista of research that is viewed as a possible way for prosumers to sell energy to *** P2P energy trading is the only method of making renewable-energy sources popular among the common *** making P2P energy trading successful,blockchain technology is sparking considerable interest among *** with smart contracts,a blockchain provides secure tamper-proof records of transactions that are recorded in distributed ledgers that are *** paper explores,using a thorough review of recently published research work,how the existing power sector is reshaping in the direction of P2P energy trading with the application of blockchain *** challenges that are being faced by researchers in the implementation of blockchain technology in the energy sector are ***,this paper presents different start-ups that have emerged in the energy-sector domain that are using blockchain *** give insight into the application of blockchain technology in the energy sector,a case of the application of blockchain technology in P2P trading in electrical-vehicle charging is *** the end,some possible areas of research in the application of blockchain technology in the energy sector are discussed.

关键词： blockchain consensus algorithms microgrid peer-to-peer energy trading distributed energy resources electric-vehicle charging