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Dependence of fluid flow on cleat aperture distribution and aperture–length scaling: a case study from Gondwana coal seams of Raniganj Formation, Eastern india

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International Journal of coal Science & Technology 2020年第1期7卷 133-146页

作者： Krishanu Bandyopadhyay Jyotirmoy Mallik Trishit Ghosh indian Institute of Science Education and Research BhopalIndia Coal India Limited.Asansol.India

Dimensions and mutual relationships amongst fracture(cleat)parameters such as maximum aperture width,average aperture width,length,spacing etc.control the connectivity within a fracture network and the fluid flow in a coal seam as the matrix permeability,here,is negligible.In this paper,we document cleat size distributions and investigate length–aperture relationships from coals of Raniganj coalfield in Eastern india.This coalfield has a proven extractable reserve of six billion tons of coal and holds immense potential to be one of the largest coal bed methane fields serving india’s growing energy needs.Here,cleat length(L)correlates with corresponding maximum aperture width(Dmax)in a power-law function with an exponent of 0.84(DmaxαL0.84)instead of the commonly observed exponents of 1 or 0.5 applicable for other natural‘opening-mode’fractures.The conventional wisdom pertains that laminar fluid flow(Q)through an isolated,smooth-walled,parallel-plate fracture,embedded in an impermeable matrix,is directly proportional to the cube of its aperture width(b,equivalent to Davg;cubic law:Qαb3).This assumes a linear relationship between length and fracture aperture.However,the modified relationship between cleat length and average aperture width changes the cubic law applicable for Raniganj coal seam and now fluid flow correlates with aperture width in a power-law function with an exponent of 4.25(Qαb4.25)instead of 3(cube).Such simplifications will come handy for the modeling and estimation of fluid flow as it will reduce the effort of cleat length measurement which is anyway difficult and can be misleading due to the risk of undersampling.

关键词： CBM Cleat coal Permeability Raniganj

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Stock market prediction using deep learning algorithms

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CAAI Transactions on Intelligence Technology 2023年第1期8卷 82-94页

作者： Somenath Mukherjee Bikash Sadhukhan Nairita Sarkar Debajyoti Roy Soumil De Nazrul Center of Social and Cultural Studies Kazi Nazrul UniversityAsansolIndia Department of Computer Science and Engineering Techno International New Town(Techno India College of Technology)KolkataIndia

The Stock Market is one of the most active research areas,and predicting its nature is an epic necessity nowadays.Predicting the Stock Market is quite challenging,and it requires intensive study of the pattern of data.Specific statistical models and artificially intelligent algorithms are needed to meet this challenge and arrive at an appropriate solution.Various machine learning and deep learning algorithms can make a firm prediction with minimised error possibilities.The Artificial Neural Network(ANN)or Deep Feedforward Neural Network and the Convolutional Neural Network(CNN)are the two network models that have been used extensively to predict the stock market prices.The models have been used to predict upcoming days'data values from the last few days'data values.This process keeps on repeating recursively as long as the dataset is valid.An endeavour has been taken to optimise this prediction using deep learning,and it has given substantial results.The ANN model achieved an accuracy of 97.66%,whereas the CNN model achieved an accuracy of 98.92%.The CNN model used 2-D histograms generated out of the quantised dataset within a particular time frame,and prediction is made on that data.This approach has not been implemented earlier for the analysis of such datasets.As a case study,the model has been tested on the recent COVID-19 pandemic,which caused a sudden downfall of the stock market.The results obtained from this study was decent enough as it produced an accuracy of 91%.

关键词： artificial neural network convolutional neural network nifty stock market

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Characterization of Almostη-Ricci–Yamabe Soliton and Gradient Almostη-Ricci–Yamabe Soliton on Almost Kenmotsu Manifolds

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Acta Mathematica Sinica,English Series 2023年第4期39卷 728-748页

作者： Somnath MONDAL Santu DEY Arindam BHATTACHARYYA Department of Mathematics Jadavpur UniversityKolkata-700032India Department of Mathematics Bidhan Chandra College Asansol-4West Bengal-713304India

The prime object in this article is to study an almostη-Ricci-Yamabe soliton and gradient almostη-Ricci-Yamabe soliton within the framework of almost Kenmotsu manifolds.It is shown that normal almost Kenmotsu manifold admitting an almostη-Ricci-Yamabe soliton or gradientη-Ricci-Yamabe soliton is locally isometric to hyperbolic space H^(2n+1)(-1).Next,we prove that if a(κ,μ)almost Kenmotsu manifold admits an almostη-Ricci-Yamabe soliton,then the manifold isη-Einstein.Besides,we find the condition for non-normal almost Kenmotsu manifolds acknowledging gradient almostη-Ricci-Yamabe soliton.Moreover,an almostη-Ricci-Yamabe soliton on(κ,μ)’-almost Kenmotsu manifold has been studied.Lastly,we construct an example of a gradient almostη-Ricci-Yamabe soliton on a 3-dimensional Kenmotsu manifold.

关键词： Ricci soliton (k μ)-almost Kenmotsu manifold (r μ)-almost Kenmotsu manifold n-Ricci-Yamabe soliton

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Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network

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Big Data Mining and Analytics 2023年第1期6卷 44-54页

作者： Amit Kumar Rai Nirupama Mandal Krishna Kant Singh Ivan Izonin Department of Electronics Engineering Indian Institute of TechnologyDhanbad(ISMDhanbad)Dhanbad 826004India Department of Electronics and Communication Engineering Asansol Engineering CollegeAsansol 713305India Department of CSE ASETAmity UniversityNoida 201301India Department of Artificial Intelligence Lviv Polytechnic National UniversityLviv 79000Ukraine

A semi supervised image classification method for satellite images is proposed in this paper.The satellite images contain enormous data that can be used in various applications.The analysis of the data is a tedious task due to the amount of data and the heterogeneity of the data.Thus,in this paper,a Radial Basis Function Neural Network(RBFNN)trained using Manta Ray Foraging Optimization algorithm(MRFO)is proposed.RBFNN is a three-layer network comprising of input,output,and hidden layers that can process large amounts.The trained network can discover hidden data patterns in unseen data.The learning algorithm and seed selection play a vital role in the performance of the network.The seed selection is done using the spectral indices to further improve the performance of the network.The manta ray foraging optimization algorithm is inspired by the intelligent behaviour of manta rays.It emulates three unique foraging behaviours namelys chain,cyclone,and somersault foraging.The satellite images contain enormous amount of data and thus require exploration in large search space.The spiral movement of the MRFO algorithm enables it to explore large search spaces effectively.The proposed method is applied on pre and post flooding Landsat 8 Operational Land Imager(OLI)images of New Brunswick area.The method was applied to identify and classify the land cover changes in the area induced by flooding.The images are classified using the proposed method and a change map is developed using post classification comparison.The change map shows that a large amount of agricultural area was washed away due to flooding.The measurement of the affected area in square kilometres is also performed for mitigation activities.The results show that post flooding the area covered by water is increased whereas the vegetated area is decreased.The performance of the proposed method is done with existing state-of-the-art methods.

关键词： Radial Basis Function Neural Network(RBFNN) Manta Ray Foraging Optimization algorithm(MRFO) Landsat 8 classification change detection disaster mitigation planning

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Design of Energy Efficient WSN Using a Noble SMOWA Algorithm

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Computers, Materials & Continua 2022年第8期72卷 3585-3600页

作者： Avishek Banerjee Deepak Garg Victor Das Laxminarayan Sahoo Ira Nath Vijayakumar Varadarajan Ketan Kotecha Department of Computer Science and Engineering Bennett UniversityGreater Noida201310India Department of Information Technology Asansol Engineering CollegeAsansol713305India Department of Computer and Information Science Raiganj UniversityRaiganj733134India Department of Computer Science and Engineering JIS College of EngineeringKalyani741235India School of Computer Science and Engineering University of New South WalesSydneyAustralia Symbiosis Centre for Applied Artificial Intelligence Symbiosis International(Deemed University)PuneIndia

In this paper,the establishment of efficientWireless Sensor Network(WSN)networks has been projected to minimize the consumption of energy using a new Self-adaptive Multi-Objective Weighted Approach(SMOWA)algorithm for solving a multi-objective problem.The Different WSN nodes deployment policies have been proposed and applied in this paper to design an efficientWireless Sensor Network to minimize energy consumption.After that,the cluster head for each cluster has been selected with the help of the duty cycle.After configuring the WSN networks,the SMOWA algorithms have been developed to obtain the minimum energy consumption for the networks.Energy minimization,as well as the amount of day-saving,has been calculated for the differentWSNswhich has been configured through different deployment policies.The major finding of the research paper is to improve the durability of Wireless Sensor Network(i)applying different deployment strategies:(Random,S pattern and nautilus shell pattern),and(ii)using a new Meta-heuristic algorithm(SMOWA Algorithm).In this research,the lifetime of WSN has been increased to a significant level.To choose the best result set from all the obtained results set some constraints such as“equivalent distribution”,“number of repetitions”,“maximum amount energy storage by a node”has been set to an allowable range.

关键词： Wireless Sensor Network(WSN) Self-adaptive Multi-Objective Weighted Approach(SMOWA) deployment strategies Meta-heuristicMethods energy minimization duty cycle

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Impact of orientation of blast initiation on ground vibrations

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第1期15卷 255-261页

作者： Dayamoy Garai Hemant Agrawal Arvind Kumar Mishra indian Institute of Technology(ISM) DhanbadIndia Central Mine Planning and Design Institute limited RanchiIndia

The blast-induced ground vibrations can be significantly controlled by varying the location and orien-tation of point of interest from blast site.The blast waves generated due to individual holes get super-imposed and resultant peak particle velocity(PPV)generates.With the orientation sequence of holes blasts on site,the superimposition angle of wave changes and hence results in significant variation in resultant PPV.The orientation with respect to the initiation of blasts resulting in lowest PPV needs to be identified for any site.By knowing the PPV contour of vibration waves in mine sites,it is possible to reduce the vibration on the structures by changing the initiation sequence.In this paper,experimental blasts were conducted at two different mine sites and the PPV values were recorded at different ori-entations from the blast site and its initiation sequence.The PPV contours were drawn to identify the orientation with least and highest PPV generation line.It was found that by merely changing the initi-ation sequence of blasts with respect to the sensitive structure or point of interest,the PPV values can be reduced significantly up to 76.9%.

关键词： Peak particle velocity(PPV) Initiation orientation Wave superimposition Orientation of blast Blast initiation

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Microfiltration,ultrafiltration and nanofiltration as a post-treatment of biological treatment process with references to oil field produced water of Moran oilfield of Assam

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Petroleum Research 2024年第1期9卷 143-154页

作者： Amarjit Rajbongshi Subrata Borgohain Gogoi Brahmaputra Valley Fertilizer Corporation limited NamrupAssamIndia Department of Petroleum Technology Dibrugarh UniversityAssamIndia

The selection of an apt technology for the treatment of Oilfield Produced Water(OFPW)depends mainly on the quality of OFPW and methods of pre-and post-treatment processes.The most challenging part of the OFPW treatment process is the removal of Suspended Solid(SS),Oil&Grease(O&G)and dissolved organics.SS and O&G pose an acute problem to the membrane filtration system by fouling the membrane surface which increases operation&maintenance costs and decreases the life of the membrane.Fouling of the membrane surface is mainly attributed to the presence of low molecular weight aromatic compounds and naphthenic acids in the suspended and dissolved organic compounds.Thus,the removal of these suspended and dissolved organic compounds before membrane filtration proffers a challenge to the researchers.In this research,bioremediation process has been applied to remove the organic compounds and the performance and fouling behaviour of hollow fibre Microfiltration(MF),Ultrafiltration(UF)and Nanofiltration(NF)membranes after the bioremediation process has been analyzed in detail.The level of toxicity was determined by comparing the pollutants with the safe discharge limit for disposal into the environment set by Central Pollution Control Board(CPCB),india.The research presents its novelty by using a hydrocarbon-degrading bacteria,Pseudomonas aeruginosa for the Reduction of Organic Loads(ROL)from OFPW of Moran oil field of Upper Assam as a pre-treatment to membrane filtration.The Total Sum Corrected Area(TSCA)method through chromatographic analyses was used for this.The organic loads removal from OFPW by the TSCA method was found to be 67-100%,100%and 100%after 7,14 and 21 days of bioremediation respectively.The major parameters in feed OFPW of Moran oil field were found to be pH(7.5-9.3),Total Dissolved Solid(TDS)(1.79-4.75)ppt,O&G(1.78-2.8)ppt,Salinity(2.94-6.98)ppt,Chloride(Cl^(-))(1.6-3.86)ppt,Bicarbonate(HCO_(3)^(-))(2.89-4.03)ppt.It was observed that the ranges of pollutants removal by NF was highest such as TDS(26-86%),sa

关键词： Oilfield produced water Organic compounds Bioremediation Membrane filtration Membrane fouling

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Navigating the intersection of psychiatry and ophthalmology:A comprehensive review of depression and anxiety management in glaucoma patients

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World Journal of Psychiatry 2024年第3期14卷 362-369页

作者： Prasanna Venkatesh Ramesh Arvind Kumar Morya Ashik Azad Pavithra Pannerselvam Aji Kunnath Devadas Sai Thaejesvi Gopalakrishnan Shruthy Vaishali Ramesh Ajanya K Aradhya Department of Glaucoma and Research Mahathma Eye Hospital Private LimitedTrichy 620017Tamil NaduIndia Department of Ophthalmology All India Institute of Medical SciencesHyderabad 508126TelanganaIndia Department of Optometry and Visual Science Mahathma Eye Hospital Private LimitedTrichy 620017Tamil NaduIndia Junior Resident Mahathma Eye Hospital Private LimitedTrichy 620017Tamil NaduIndia Department of Cataract and Refractive Surgery Mahathma Eye Hospital Private LimitedTrichy 620017Tamil NaduIndia

Glaucoma,a prevalent and debilitating eye disease,has long been associated with vision impairment and blindness.However,recent research has shed light on the often-underestimated psychological dimensions of this condition.Anxiety and depression,two pervasive psychiatric comorbidities,have been increasingly recognized among glaucoma patients.This comprehensive review aims to explore the intricate relationship between psychiatry and ophthalmology,in the context of managing depression and anxiety in glaucoma patients.By meticulously examining peer-reviewed literature,we synthesize current knowledge on the prevalence,risk factors,and underlying mechanisms of anxiety and depression in glaucoma.The evidence reveals that glaucoma patients face an elevated risk of experiencing these mood disorders.Factors such as progressive vision loss,complex medication regimens,and the fear of further visual deterioration contribute to their vulnerability.Moreover,we delve into the bidirectional relationship between glaucoma and mood disorders,shedding light on the complex interplay between ocular and emotional health.Our review investigates the implications of anxiety and depression on glaucoma management,including their potential impact on treatment adherence,disease progression,and overall quality of life.We also explore the neurobiological pathways linking glaucoma and mood disorders,providing a foundation for future research and potential therapeutic interventions.In conclusion,recognizing the psychological burden carried by glaucoma patients is essential for holistic and patient-centered care.This review underscores the pressing need for integrated approaches that bring together ophthalmological and psychiatric expertise to optimize the well-being of individuals facing the challenges of glaucoma.By addressing anxiety and depression in glaucoma care,healthcare providers can enhance the overall quality of life for these patients,ultimately leading to improved outcomes and a brighter future for those affected by this condition.This

关键词： Glaucoma Psychiatry Depression Anxiety Risk factors Bidirectional relationship

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Sequence Stratigraphic Model of Middle Permian Barakar Formation from a Marginal Gondwana Basin, india

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Journal of Earth Science 2018年第4期29卷 745-754页

作者： Joyjit Dey Souvik Sen coal india limited Central Mine Planning and Design Institute (CMPD1) Regional Institute-3 Jharkhand 829 103 India Geologix limited Dynasty Building Level-4 Wing-A Andheri Kurla Road Andheri (E) Mumbai 400 059 India

Gondwana deposits are extensively found across the continents. Here we study the Mid- dle Permian Barakar Formation from the marginal Gondwana Basin, eastern india, being deposited in a normal fault setting. Availability of extensive cores as well as geophysical log suites （gammaresistivity-density from drilled wells） from the study area helped us achieving high resolution interpretation. Core study identifies fluvial sedimentary architectures, which were correlated with the geophysical logs and modeled field-wide to understand vertical and horizontal facies disposition. The facies analysis has been used to establish a sequence stratigraphic model of the cyclic Barakar deposition. Four major fining upward depositional sequences were identified, each sequence comprises of low accommodation system tract （LAST） at base and high accommodation system tract （HAST） at top. LAST is characterized by vertically stacked, multistory amalgamated channel sandstone dominated facies, while floodplain dominated facies characterizes HAST, reflecting a gradual shift from braided to meandering depositional system from bottom to top of each cycle. Study reveals depocenter to be in the western part, supported by eastward thinning of sediment packets, all being deposited in a halfgraben setting.

关键词： fluvial sequence stratigraphy Gondwana sediment Middle Permian Barakar Formation.

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Chimney ImplosionmA Case Study

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Journal of Geological Resource and Engineering 2014年第1期2卷 32-38页

作者： Ajay Kumar Jha Central Mine Planning and Design Institute Coal India Limited Ranchi 834008 India

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