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Browsing by Author "Kumar, M"

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Areservoir computing approach for forecasting and regenerating both dynamical andtime-delay controlled financial system behavior
(2021-02) Budhiraja, R; Kumar, M
Significant research in reservoir computing over the past two decades has revived interest in recurrent neural networks. Owing to its ingrained capability of performing high-speed and low-cost computations this has become a panacea for multi-variate complex systems hav ing non-linearity within their relationships. Modelling economic and financial trends has always been achallenging task owing to their volatile nature and no linear dependence on associated influencers. Prior studies aimed at effectively forecasting such financial systems, but, always left a visible room for optimization in terms of cost, speed and modelling com plexities. Our work employs a reservoir computing approach complying to echo-state net work principles, along with varying strengths of time-delayed feedback to model a complex financial system. The derived model is demonstrated to act robustly towards influence of trends and other fluctuating parameters by effectively forecasting long-term system behav ior. Moreover, it also re-generates the financial system unknowns with a high degree of accuracy when only limited future data is available, thereby, becoming a reliable feeder for any long-term decision making or policy formulations.
Assessment and Mapping of Riverine Flood Susceptibility (RFS) in India through Coupled Multicriteria Decision Making Models and Geospatial Techniques
(2023-11) Kumar, R; Kumar, M; Tiwari, A
Abstract: Progressive environmental and climatic changes have significantly increased hydrometeo rological threats all over the globe. Floods have gained global significance owing to their devastating impact and their capacity to cause economic and human loss. Accurate flood forecasting and the identification of high-risk areas are essential for preventing flood impacts and implementing strategic measures to mitigate flood-related damages. In this study, an assessment of the susceptibility to riverine flooding in India was conducted utilizing Multicriteria Decision making (MCDM) and an extensive geospatial database was created through the integration of fourteen geomorphological, meteorological, hydroclimatic, and anthropogenic factors. The coupled methodology incorporates a Fuzzy Analytical Hierarchy Process (FAHP) model, which utilizes Triangular Fuzzy Numbers (TFN) to determine the Importance Weights (IWs) of various parameters and their subclasses based on the Saaty scale. Based on the determined IWs, this study identifies proximity to rivers, drainage density, and mean annual rainfall as the key factors that contribute significantly to the occurrence of riverine floods. Furthermore, as the Geographic Information System (GIS) was employed to create the Riverine Flood Susceptibility (RFS) map of India by overlaying the weighted factors, it was found that high, moderate, and low susceptibility zones across the country span of 15.33%, 26.30%, and 31.35% of the total area of the country, respectively. The regions with the highest susceptibility to flooding are primarily concentrated in the Brahmaputra, Ganga, and Indus River basins, which happen to encompass a significant portion of the country’s agricultural land (334,492 km2 ) potentially posing a risk to India’s food security. Approximately 28.13% of built-up area in India falls in the highly susceptible zones, including cities such as Bardhaman, Silchar, Kharagpur, Howrah, Kolkata, Patna, Munger, Bareilly, Allahabad, Varanasi, Lucknow, and Muzaffarpur, which are particularly susceptible to flooding. RFS is moderate in the Kutch-Saurashtra-Luni, Western Ghats, and Krishna basins. On the other hand, areas on the outskirts of the Ganga, Indus, and Brahmaputra basins, as well as the middle and outer portions of the peninsular basins, show a relatively low likelihood of riverine flooding. The RFS map created in this research, with an 80.2% validation accuracy assessed through AUROC analysis, will function as a valuable resource for Indian policymakers, urban planners, and emergency management agencies. It will aid them in prioritizing and executing efficient strategies to reduce flood risks effectively.
Comparison of the binding energies of approved mpox drugs and phytochemicals through molecular docking, molecular dynamics simulation, and ADMET studies: An in silico approach
(2023-09) Kumar, M; Ansari, A
The mpox (previously monkeypox) outbreak in more than 100 non-endemic countries in 2022 posed a serious global health concern. Mpox is emerging as a global public health threat from a seemingly neglected disease. A42R profilin-like protein from mpox virus (PDB ID: 4QWO) could be a preferred target lead. The binding affinity of commonly used drugs/mAbs (tecovirimat, brincidofovir, cidofovir) for A42R profilin-like protein was examined in silico through molecular docking. Further, the results were com pared with those of the phytochemicals curcumin, rutin, and theaflavin. Tecovirimat ( 7.31 kcal/mol, IC50 = 4.39 lM) and theaflavin ( 6.99 kcal/mol, IC50 = 7.54 lM) had the highest affinities. Molecular dynamics simulation of the theaflavin–4QWO complex was performed to ascertain the stability of ligand–protein interactions in natural charge, molecular electrostatic potential, and frontier molecular orbital analyses. The predicted QSAR and pharmacokinetic properties of all compounds were evaluated to find a suitable candidate for designing and developing new drugs. The evaluated log P values for brin cidofovir and tecovirimat were higher than those of the other drugs in the QSAR study. Theaflavin had an impressive log P of 4.77, which hints at its high biological activity. The findings recommend further in vitro experimental validation to develop potential low-cost mpox therapies.
An efficient framework for secure data transmission using blockchain in IoT environment
(2023-12) Bhattacharjee, S; Gangwar, S; Kumar, M; Saini, K; Saini, R; Chauhan, S; Pandey, K; Goyal, N
The secure and efficient sharing of data has been recognised as a significant concern in Internet of Things (IoT)-enabled smart systems, including smart cities, smart agriculture, and smart health applications. Smart systems utilise a substantial quantity of IoT devices, which in turn generate a significant volume of data. Internet of Things (IoT) devices typically possess constrained storage and processing capacities, making the implementation of security measures on such devices a difficult task. This paper presents a framework for secure data transmission using blockchain (SDTUB) for blockchain-based IoT systems, with a focus on enhancing data security. The use of clustered authorization aims to enhance the interoperability of IoT authorization. The central blockchain is employed for permission purposes concerning cluster management nodes, whereas the regional blockchain suffices for authorization of regular nodes. The proposed mechanism is implemented using MATLAB, and the performance is analysed using performance metrics such as energy consumption and objective value. In the proposed mechanism, the energy consumption is low compared to the AuBWSN technique.
An efficient framework for secure data transmission using blockchain in IoT environment
(2023-12) Bhattacharjee, S; Gangwar, S; Kumar, M; Saini, K; Saini, R; Chauhan, S; Pandey, K; Essah, R; Goya, N
The secure and efficient sharing of data has been recognised as a significant concern in Internet of Things (IoT)-enabled smart systems, including smart cities, smart agriculture, and smart health applications. Smart systems utilise a substantial quantity of IoT devices, which in turn generate a significant volume of data. Internet of Things (IoT) devices typically possess constrained storage and processing capacities, making the implementation of security measures on such devices a difficult task. This paper presents a framework for secure data transmission using blockchain (SDTUB) for blockchain-based IoT systems, with a focus on enhancing data security. The use of clustered authorization aims to enhance the interoperability of IoT authorization. The central blockchain is employed for permission purposes concerning cluster management nodes, whereas the regional blockchain suffices for authorization of regular nodes. The proposed mechanism is implemented using MATLAB, and the performance is analysed using performance metrics such as energy consumption and objective value. In the proposed mechanism, the energy consumption is low compared to the AuBWSN technique.
An efficient synthesis towards the core of Crinipellin: TD-DFT and docking studies
(2021-01) Sahu, R; Mohapatra, R; Al-Resayes, S; Das, D; Parhie, P; Rahman, S; Pintilie, L; Kumar, M; Azam, M; Ansari, A
In this present report, we are describing a novel route for the synthesis of the tetracyclic ring systems, a common core of crinipellin, via oxidative dearomatization, cycloaddition and oxa di-pi-methane rearrangement. We are also concerned to explore a route to tetracyclic core (1e)of Crinipellin and tricyclic core (1g) of Allicaol B through intermolecular diels alder reaction and pho tochemically 1,2 acyl shift. Moreover, docking study of compound 13 and 16 is investigated against AcrB multidrug efflux pump of Escherichia coli (PDB ID: 1T9U), main protease of SARS COV-2 (PDB ID: 6W63), DNA gyrase of Streptococcus pneumonia (PDB ID: 4Z2C), human estrogen receptor alpha (PDB ID: 3ERT), human lanosterol 14-alpha-demethylase (CYP51)(PDB ID: 3JUS) and cyclooxygenase-2 (Prostaglandin Synthase-2) (PDB ID: 1CX2). The obtained results are important for the exploitation of the therapeutic potential of these derivatives as antimicrobial, antiviral, anticancer, antifungal or anti-inflammatory agents. In addition, TD-DFT studies of the compounds are also carried out.
GMPP Tracking of Solar PV system using Spotted Hyena and Quadratic Approximation based Hybrid Algorithm under Partially shaded conditions
(2023) Kumar, P; Kumar, M; Bansal, A
The demand for clean and renewable energy is increasing due to environmental concerns. Photovoltaic (PV) system is very popular from the renewable sources and its usage is increasing. The PV system power transfer efficiency depends on several factors such electrical characteristics of loads, solar irradiation, shading condition and panel temperature. The process of transferring maximum possible power to load from PV system by adjusting the system parameters is called maximum power point tracking (MPPT). Under the partially shaded conditions, multiple power peaks are created in the PV curves and makes the MPPT is a non-convex problem. It is a challenging problem to track the global maximum power point (GMPP) under partially shaded conditions. It is essential to recognize the GMPP and restart the string as early as possible to prevent the physical as well as economical damage. In this paper, a new hybrid algorithm for MPPT is proposed and called as QASHO, a combination of Spotted Hyena optimization (SHO) and Quadrature approximation (QA) technique. The QASHO is used to track the GMPP under different weather conditions such as partial shading. The simulation results are compared with Perturb and Observe (P&O) algorithm and Cuckoo Search optimization (CSO) algorithm and promised for better performance in tracking GMPP. The experimental results are provided to validate the proposed MPPT methodology.
Groundwater Quality assessment for Drinking Purpose using Traditional and Fuzzy-GIS based Water Quality Index in Gurugram District of Haryana, India
(2023-05) Tiwari, A; Kumar, M; Thakur, S
Primarily groundwater is consumed for the drinking and irrigation purpose. However, due to increasing anthropogenic activities, its quality and quantity have substantially declined over time. The focus of this study is to evaluate the pre-monsoonal groundwater quality and its spatial variability for drinking purposes in the Gurugram, Haryana, India. Ground Water Quality Index (GWQI) developed on the basis of the Geographical Information System is effective in the assessment of groundwater quality and its spatial variability, but it is unable to account for uncertainties related to environmental problems. Thus, a Hybrid Fuzzy-GIS based Water Quality Index (FGQI) has been proposed for the assessment of groundwater quality. The study conducted factor analysis to identify the prime factors responsible for groundwater contamination and collected pre-monsoonal groundwater samples through primary sampling. The groundwater quality was assessed based on eight hydro geochemical parameters (pH, TDS, Calcium, Chloride, Sulphate, Fluoride, Potassium, and Sodium). The spatial interpolation of each parameter was performed using appropriate techniques, selected based on a normality test. The guidelines of the World Health Organization (WHO) and Bureau of Indian Standard (BIS) were incorporated in the development of GWQI and FGQI, respectively. Correlation analysis was performed to determine the best fuzzy overlay technique for FGQI, and the Fuzzy GAMMA technique with gamma equal to 0.9 was selected. Finally, the GWQI and FGQI were classified into three classes: unsuitable, moderate suitable, and suitable using "natural break." A higher index indicates a higher water quality. The results show that the groundwater in the central part of Gurugram is suitable for drinking, while it is not suitable in the extreme north, south-east, and western regions. In conclusion, this study finds that FGQI effectively assesses the groundwater quality in the region better than GWQI.
Groundwater Quality assessment for Drinking Purpose using Traditional and Fuzzy-GIS based Water Quality Index in Gurugram District of Haryana, India
(2023-05) Tiwari, A; Kumar, M; Thakur, S
Primarily groundwater is consumed for the drinking and irrigation purpose. However, due to increasing anthropogenic activities, its quality and quantity have substantially declined over time. The focus of this study is to evaluate the pre-monsoonal groundwater quality and its spatial variability for drinking purposes in the Gurugram, Haryana, India. Ground Water Quality Index (GWQI) developed on the basis of the Geographical Information System is effective in the assessment of groundwater quality and its spatial variability, but it is unable to account for uncertainties related to environmental problems. Thus, a Hybrid Fuzzy-GIS based Water Quality Index (FGQI) has been proposed for the assessment of groundwater quality. The study conducted factor analysis to identify the prime factors responsible for groundwater contamination and collected pre-monsoonal groundwater samples through primary sampling. The groundwater quality was assessed based on eight hydro geochemical parameters (pH, TDS, Calcium, Chloride, Sulphate, Fluoride, Potassium, and Sodium). The spatial interpolation of each parameter was performed using appropriate techniques, selected based on a normality test. The guidelines of the World Health Organization (WHO) and Bureau of Indian Standard (BIS) were incorporated in the development of GWQI and FGQI, respectively. Correlation analysis was performed to determine the best fuzzy overlay technique for FGQI, and the Fuzzy GAMMA technique with gamma equal to 0.9 was selected. Finally, the GWQI and FGQI were classified into three classes: unsuitable, moderate suitable, and suitable using "natural break." A higher index indicates a higher water quality. The results show that the groundwater in the central part of Gurugram is suitable for drinking, while it is not suitable in the extreme north, south-east, and western regions. In conclusion, this study finds that FGQI effectively assesses the groundwater quality in the region better than GWQI.
Integrated Spatial Analysis of Forest Fire Susceptibility in the Indian Western Himalayas (IWH) Using Remote Sensing and GIS-Based Fuzzy AHP Approach
(2023-09) Pragya; Kumar, M; Tiwari, A; Majid, SI; Bhadwal, S
Forest fires have significant impacts on economies, cultures, and ecologies worldwide. Developing predictive models for forest fire probability is crucial for preventing and managing these fires. Such models contribute to reducing losses and the frequency of forest fires by informing prevention efforts effectively. The objective of this study was to assess and map the forest fire susceptibility (FFS) in the Indian Western Himalayas (IWH) region by employing a GIS-based fuzzy analytic hierarchy process (Fuzzy-AHP) technique, and to evaluate the FFS based on forest type and at district level in the states of Jammu and Kashmir, Himachal Pradesh, and Uttarakhand. Seventeen potential indicators were chosen for the vulnerability assessment of the IWH region to forest fires. These indicators encompassed physiographic factors, meteorological factors, and anthropogenic factors that significantly affect the susceptibility to fire in the region. The significant factors in FFS mapping included FCR, temperature, and distance to settlement. An FFS zone map of the IWH region was generated and classified into five categories of very low, low, medium, high, and very high FFS. The analysis of FFS based on the forest type revealed that tropical moist deciduous forests have a significant vulnerability to forest fire, with 86.85% of its total area having very high FFS. At the district level, FFS was found to be high in sixteen districts and very high in seventeen districts, constituting 25.7% and 22.6% of the area of the IWH region. Particularly, Lahul and Spiti had 63.9% of their total area designated as having very low FSS, making it the district least vulnerable to forest fires, while Udham Singh Nagar had a high vulnerability with approximately 86% of its area classified as having very high FFS. ROC-AUC analysis, which provided an appreciable accuracy of 79.9%, was used to assess the validity of the FFS map produced in the present study. Incorporating the FFS map into sustainable development planning will assist in devising a holistic strategy that harmonizes environmental conservation, community safety, and economic advancement. This approach can empower decision makers and relevant stakeholders to take more proactive and informed actions, promoting resilience and enhancing long-term well-being.
Integrated Spatial Analysis of Forest Fire Susceptibility in the Indian Western Himalayas (IWH) Using Remote Sensing and GIS-Based Fuzzy AHP Approach
(2023-09) Pragya; Kumar, M; Tiwari, A
Forest fires have significant impacts on economies, cultures, and ecologies worldwide. Developing predictive models for forest fire probability is crucial for preventing and managing these fires. Such models contribute to reducing losses and the frequency of forest fires by informing prevention efforts effectively. The objective of this study was to assess and map the forest fire susceptibility (FFS) in the Indian Western Himalayas (IWH) region by employing a GIS-based fuzzy analytic hierarchy process (Fuzzy-AHP) technique, and to evaluate the FFS based on forest type and at district level in the states of Jammu and Kashmir, Himachal Pradesh, and Uttarakhand. Seventeen potential indicators were chosen for the vulnerability assessment of the IWH region to forest fires. These indicators encompassed physiographic factors, meteorological factors, and anthropogenic factors that significantly affect the susceptibility to fire in the region. The significant factors in FFS mapping included FCR, temperature, and distance to settlement. An FFS zone map of the IWH region was generated and classified into five categories of very low, low, medium, high, and very high FFS. The analysis of FFS based on the forest type revealed that tropical moist deciduous forests have a significant vulnerability to forest fire, with 86.85% of its total area having very high FFS. At the district level, FFS was found to be high in sixteen districts and very high in seventeen districts, constituting 25.7% and 22.6% of the area of the IWH region. Particularly, Lahul and Spiti had 63.9% of their total area designated as having very low FSS, making it the district least vulnerable to forest fires, while Udham Singh Nagar had a high vulnerability with approximately 86% of its area classified as having very high FFS. ROC-AUC analysis, which provided an appreciable accuracy of 79.9%, was used to assess the validity of the FFS map produced in the present study. Incorporating the FFS map into sustainable development planning will assist in devising a holistic strategy that harmonizes environmental conservation, community safety, and economic advancement. This approach can empower decision makers and relevant stakeholders to take more proactive and informed actions, promoting resilience and enhancing long-term well-being.
Need for rating system for assessing sustainability of built environment during construction stage
(2023-06) Dubey, MK; Raj, V; Kumar, M; Garg, V
Sustainability in construction has gained attention in recent years as the construction industry adversely impacts the environment and green construction has been emphasized. Various rating systems have been developed by various organizations across the world like LEED, USA; CASBEE), Japan; BREEMA, UK; GBCSL, Sri Lanka, IGBC, India; etc. to certify construction projects under the green projects category, based on parameters majorly considering three factors environmental, societal & economic impact during the entire span of a project from inception stage to demolition stage. In these sustainability assessment rating systems, the parameters relevant to the construction phase have not been emphasized except for a few factors which have been considered under pre‐requisite. Though the construction phase has a comparatively shorter duration, it adversely impacts sustainability if considered collectively. So, a holistic approach is needed for sustainability assessment which shall include construction stage‐based sustainability parameters too. In this paper, with a questionnaire survey & interaction with experts, the need for construction‐based sustainability parameters has been discussed for making a holistic sustainability assessment rating system. The survey & interaction data were analyzed with an analytical hierarchical process (AHP) to understand the need for the additional parameter during the construction stage of the project.
Need for rating system for assessing sustainability of built environment during construction stage
(2023-06) Dubey, M; Raj, V; Kumar, M; Garg, V
Sustainability in construction has gained attention in recent years as the construction industry adversely impacts the environment and green construction has been emphasized. Various rating systems have been devel oped by various organizations across the world like LEED, USA; CASBEE), Japan; BREEMA, UK; GBCSL, Sri Lanka, IGBC, India; etc. to certify construction projects under the green projects category, based on parameters majorly considering three factors environmental, societal & economic impact during the entire span of a project from inception stage to demolition stage. In these sustainability assessment rating systems, the parameters rel evant to the construction phase have not been emphasized except for a few factors which have been considered under pre‐requisite. Though the construction phase has a comparatively shorter duration, it adversely impacts sustainability if considered collectively. So, a holistic approach is needed for sustainability assessment which shall include construction stage‐based sustainability parameters too. In this paper, with a questionnaire survey & interaction with experts, the need for construction‐based sustainability parameters has been discussed for making a holistic sustainability assessment rating system. The survey & interaction data were analyzed with an analytical hierarchical process (AHP) to understand the need for the additional parameter during the con struction stage of the project
A new parameter estimation method for the extended power Lindley distribution based on order statistics, with application
(2024-06) Kumar, D; Kumar, M; Yadav, S; Goyal, A
In this paper, we propose inference procedures for the estimation of parameters by using or der statistics. First, we derive some new expressions for single and product moments of the order statistics from the extended power Lindley distribution. We then use these moments to obtain the best linear unbiased estimates (BLUEs) of the location and scale parameters based on Type-II right-censored samples. A real data set is analysed to illustrate the flexibility and importance of the model.
Photovoltaic (PV) Parameter Extraction using a Hybrid Algorithm based on Spotted Hyena-Ant Lion Optimization
(2023-12) Kumar, P; Kumar, M; Bansal, A
The parameter extraction of Photovoltaic (PV) cell and module is a necessary to simulate and evaluate the performance of the PV system. The parameter extraction is a complex and challenging task due to its non-linear nature. Researchers are used several metaheuristic algorithms to solve the non-linear problem of parameter extraction. However, the demand for most accurate and reliable methods is increasing to get precise estimation of parameters. In this paper, a novel hybrid optimization algorithm is proposed based on the Spotted-Hyena optimization (SHO) and Ant Lion Optimization (ALO). The hybrid method is called as Spotted Hyena – Ant Lion (SH-AL) optimization. The optimization algorithm is applied in two stages. In stage 1, essential parameters are identified and extracted using SHO and passed to stage 2. In stage 2, identified parameters are optimized using ALO for accurate model of PV cell. Different type of PV cells such as thin film, mono and multi crystalline are examined under various irradiance conditions to extract the parameters. The proposed algorithm is validated by comparing the results with other algorithms and proposed algorithm is proved its superiority.
Relativistic modeling of stellar objects in a Schwarzschild’s coordinates with embedded class one spacetime
(2023-06) Prasad, AK; Kumar, M; Kumar, J
In this study, we investigate a new relativistic anisotropic Einstein field equations solution for compact stars under embedding class 1 conditions. In order to do this, we apply the Karmarkar condition and the embedding class one technique. By taking Buchdahl type metric poten tial grr into consideration, the precise analytical solution has been investigated. We have studied physical characteristics of various compactstarusingthisanalytical solution. Central singularities are absent from the solution. We have explored thermodynamic observables inside the stellar models, such as radial and tangential pressures, matter density, anisotropic factor, energy conditions, TOV, red-shift, and the speed of sound, etc., after establishing this space-time geometry for the stellar models. From the graphical representation of vari ousphysicalcharacteristics,itisdemonstratedthatourmodel meets all the specification for ultra-high density compact bodies.
Relativistic modeling of stellar objects in a Schwarzschild’s coordinates with embedded class one spacetime
(2023-06) Prasad, A; Kumar, M; Kumar, J
In this study, we investigate a new relativistic anisotropic Einstein field equations solution for compact stars under embedding class 1 conditions. In order to do this, we apply the Karmarkar condition and the embedding class one technique. By taking Buchdahl type metric poten tial grr into consideration, the precise analytical solution has been investigated. We have studied physical characteristics of various compact star using this analytical solution. Central singularities are absent from the solution. We have explored thermodynamic observables inside the stellar models, such as radial and tangential pressures, matter density, anisotropic factor, energy conditions, TOV, red-shift, and the speed of sound, etc., after establishing this space-time geometry for the stellar models. From the graphical representation of vari ous physical characteristics, it is demonstrated that our model meets all the specification for ultra-high density compact bodies.
Renewable Energy: Potential, Status, Targets and Challenges in Rajasthan
(2020) Bhukya, M; Kumar, M; Kant, A; Punit
India has a population of 1.3 billion people and one of largest growing economies in the world. Therefore, there is a strong demand of energy. Till date, the main source of energy is coal which is non renewable and harmful to the environment. Therefore, it is important and necessary to find an alternative source of energy. This indirectly drives us to focus on Renewable Energy Source, which has several advantages. The Ministry of National Renewable Energy (MNRE) has launched many schemes to encourage the domestic and commercial sector to use renewable energy sources. In India the state of Rajasthan is occupying 5th position in the production of electric power generation from Renewable Energy Sources like Solar, Wind and Biomass etc. Therefore this paper discusses the potential and opportunities of electric power generation through renewable energy in the state of Rajasthan.

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