Search results for: Vikrant Sinha

Authors: Prawal Sinha, Peeyush Singh, Pravir Dutt

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Problems in elastohydrodynamic lubrication have attracted a lot of attention in the last few decades. Solving a two-dimensional problem has always been a big challenge. In this paper, a new discontinuous finite volume method (DVM) for two-dimensional point contact Elastohydrodynamic Lubrication (EHL) problem has been developed and analyzed. A complete algorithm has been presented for solving such a problem. The method presented is robust and easily parallelized in MPI architecture. GMRES technique is implemented to solve the matrix obtained after the formulation. A new approach is followed in which discontinuous piecewise polynomials are used for the trail functions. It is natural to assume that the advantages of using discontinuous functions in finite element methods should also apply to finite volume methods. The nature of the discontinuity of the trail function is such that the elements in the corresponding dual partition have the smallest support as compared with the Classical finite volume methods. Film thickness calculation is done using singular quadrature approach. Results obtained have been presented graphically and discussed. This method is well suited for solving EHL point contact problem and can probably be used as commercial software.

Keywords: elastohydrodynamic, lubrication, discontinuous finite volume method, GMRES technique

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Authors: Tauhidur Rahman, Arnab Kumar Sinha

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This paper presents a comparative study of Arch bridges based on their varying rise to span ratio. The comparison is done between different steel Arch bridges which have variable span length and rise to span ratio keeping the same support condition. The aim of our present study is to select the optimum value of rise to span ratio of Arch bridge as the cost of the Arch bridge increases with the increasing of the rise. In order to fulfill the objective, several rise to span ratio have been considered for same span of Arch bridge and various structural parameters such as Bending moment, shear force etc have been calculated for different model. A comparative study has been done for several Arch bridges finally to select the optimum rise to span ratio of the Arch bridges. In the present study, Finite Element model for medium to long span, with different rise to span ratio have been modeled and are analyzed with the help of a Computational Software named MIDAS Civil to evaluate the results such as Bending moments, Shear force, displacements, Stresses, influence line diagrams, critical loads. In the present study, 60 models of Arch bridges for 80 to 120 m span with different rise to span ratio has been thoroughly investigated.

Keywords: arch bridge, analysis, comparative study, rise to span ratio

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Authors: Srinivasarao Kondaparla, Utsab Debnath, Awakash Soni, Vasantha Rao Dola, Manish Sinha, Kumkum Kumkum Srivastava, Sunil K. Puri, Seturam B. Katti

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In a focused exploration, we have designed synthesized and biologically evaluated chiral conjugated new chloroquine (CQ) analogs with substituted piperazines as antimalarial agents. In vitro as well as in vivo studies revealed that compound 7c showed potent activity [for in vitro IC₅₀= 56.98nM (3D7), 97.76nM (K1); for in vivo (up to at the dose of 12.5 mg/kg); SI = 3510] as a new lead of antimalarial agent. Other compounds 6b, 6d, 7d, 7h, 8c, 8d, 9a, and 9c are also showing moderate activity against CQ-sensitive (3D7) strain and superior activity against resistant (K1) strain of P. falciparum. Furthermore, we have carried out docking and 3D-QSAR studies of all in-house data sets (168 molecules) of chiral CQ analogs to explain the structure activity relationships (SAR). Our new findings specified the significance of H-bond interaction with the side chain of heme for biological activity. In addition, the 3D-QSAR study against 3D7 strain indicated the favorable and unfavorable sites of CQ analogs for incorporating steric, hydrophobic and electropositive groups to improve the antimalarial activity.

Keywords: piperazines, CQ-sensitive strain-3D7, in-vitro and in-vivo assay, docking, 3D-QSAR

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Authors: Amitkumar Barot, Vijaykumar Sinha

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There is growing interest in the development of new materials based on recycled polymers from plastic waste, and also in the field of lubricants much effort has been spent on substitution of petro-based raw materials by natural-based renewable ones. This is due to the facts of depleting fossil fuels and due to strict environmental laws. In relevance to this, new technique for the formulation of grease that combines the chemical recycling of poly (ethylene terephthalate) PET with the use of castor oil (CO) has been developed. Comparison to diols used in chemical recycling of PET, castor oil is renewable, easily available, environmentally friendly, economically cheaper and hence sustainability indeed. The process parameters like CO concentration and temperature were altered, and further, the influences of the process parameters have been studied in order to establish technically and commercially viable process. Further thereby formed depolymerized product find an application as base oil in the formulation of grease. A depolymerized product has been characterized by various chemical and instrumental methods, while formulated greases have been evaluated for its tribological properties. The grease formulated using this new environmentally friendly approach presents applicative properties similar, and in some cases superior, compared to those of a commercial grease obtained from non-renewable resources.

Keywords: castor oil, grease formulation, recycling, sustainability

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Authors: Anthony Chidi Ezika, Gbolahan Joseph Adekoya, Emmanuel Rotimi Sadiku, Yskandar Hamam, Suprakas Sinha Ray

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High-energy-density polymer/ceramic composites require a high breakdown strength and dielectric constant. Interface polarization and electric percolation are responsible for the high dielectric constant. In order to create composite dielectrics, high conductivity ceramic particles are combined with polymers to increase the dielectric constant. In this study, bonding and the non-uniform distribution of charges in the ceramic/ceramic interface zone are investigated using density functional theory (DFT) modeling. This non-uniform distribution of charges is intended to improve the ceramic/ceramic interface's dipole polarization (dielectric response). The interfacial chemical bond formation can also improve the structural stability of the hybrid filler and, consequently, of the composite films. To comprehend the electron-transfer process, the density of state and electron localization function of the PPy with hybrid fillers are also studied. The polymer nanocomposite is anticipated to provide a suitable dielectric response for energy storage applications.

Keywords: energy storage, V₂C/ ZnS hybrid, polypyrrole, MXene, nanocomposite, dielectric

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Authors: Parul Sinha

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Electronic commerce facilitates increased choice and information on goods or services for consumers but at the same time it compounds the inequality of bargaining power many consumers face when contracting with sellers. Due to the ‘inequality of bargaining power’ experienced by consumers when contracting by electronic means with business sellers in different jurisdictions, it may be difficult to determine where either the consumer is domiciled or the place where the seller is situated or conducts its business. The question arises in such situation that if one party wants to sue the other, then where can one sue? Which court has jurisdiction to try international conflicts arising from electronic contracts concluded through the internet? Will the same rules applicable to conventional contracts apply? Or should other considerations be taken into account? In all these situations the degree of consumer protection in electronic contracts comes into picture. In the light of the above, the paper discusses the jurisdiction and choice of law rules applied in EU and United States. Further, the paper considers the current uncertainty plaguing questions of jurisdiction in India. Therefore, the jurisdiction and choice of law rules for electronic contracts must be applied consistently and provide an automatic, harmonised rule in favour of the consumer’s jurisdiction and law. Lastly, the paper suggests the need for a uniform law in order to achieve effective juridical protection.

Keywords: electronic commerce, electronic contracts, jurisdiction, consumer protection

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Authors: Astha Sinha, Anjali Kanagali

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The United Kingdom’s withdrawal from the European Union, also termed as “Brexit,” took place on June 23, 2016 and immediately had global repercussions on the stock markets of the world. It is however expected to have a greater impact on the Banking sector in the UK. There is a two-fold effect on the earnings of banks which is being expected. First is of the trading activity and investment banking businesses being hit due to global weakness in financial markets. Second is that the banks having a large presence in the European Union will have to restructure their operations in order to cover other European countries as well increase their operating costs. As per the analysis, banks are expected to face rate cuts, bad loans, and tight liquidity. The directives in the Brexit negotiations on the Markets in Financial Instruments Directive (MiFID) will be a major decision to be taken for the Banking sector. New regulations will be required since most of the regulations governing the financial services industry allowing for the cross-border transactions were at the EU level. This paper aims to analyze the effect of Brexit on the UK Banking sector and changes in regulations that are expected due to the same. It shall also lay down the lessons learnt from the 2008 financial crisis and draw a parallel in terms of potential areas to be focused on for revival of the financial sector of Britain.

Keywords: Brexit, Brexit impact on UK, impact of Brexit on banking, impact of Brexit on financial services

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Authors: Yu-Ting Chen, Shiao-Shing Chen, Hung-Te Hsu, Saikat Sinha Ray

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Forward osmosis (FO) is a crucial technology with low operating pressure and cost for water reuse and reclamation. In Taiwan, with the advance of science and technology, thin film transistor liquid crystal displays (TFT-LCD) based industries are growing exponentially. In the optoelectronic industry wastewater, the iodide is one of the valuable element; it is also used in the medical industry. In this study, it was intended to concentrate iodide by utilizing FO system and can be reused for TFT-LCD production. Cellulose triacetate (CTA) membranes were used for all these FO experiments, and potassium iodide solution was used as the feed solution. It has been found that EDTA-2Na as draw solution at pH 8 produced high water flux and minimized salt leakage. The result also demonstrated that EDTA-2Na of concentration 0.6M could achieve the highest water flux (6.69L/m2 h). Additionally, from the recovered iodide ion from pH 3-8, the I- species was found to be more than 99%, whereas I2 was measured to be less than 1%. When potassium iodide solution was used from low to high concentration (1000 ppm to 10000 ppm), the iodide rejection was found to be than more 90%. Since, CTA membrane is negatively charged and I- is anionic in nature, so it will from electrostatic repulsion and hence there will be higher rejection. The overall performance demonstrates that recovery of concentrated iodide using FO system is a promising technology.

Keywords: draw solution, EDTA-2Na, forward osmosis, potassium iodide

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Authors: Roshani Gusain, Deep Sinha, Karan Nayal, Anmol Kumar Mishra, Manav Singh

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In this research paper, we introduce "Mind Care Assistant - Companion App", which is a Flutter and Firebase-based mental health monitor. The app wants to improve and monitor the mental health of its users, it uses noninvasive ways to check for a change in their emotional state. By responding to questions, the app will provide individualized suggestions ᅳ tasks and mindfulness exercises ᅳ for users who are depressed or anxious. The app features a chat-bot that incorporates cognitive behavioural therapy (CBT) principles and combines natural language processing with machine learning to develop personalised responses. The feature of the app that makes it easy for us to choose between iOS and Android is cross-platform, which allows users from both mobile systems to experience almost no changes in their interfaces. With Firebase integration synchronized and real-time data storage, security is easily possible. The paper covers the architecture of the app, how it was developed and some important features. The primary research result presents the promise of a "Mind Care Assistant" in mental health care using new wait-for-health technology, proposing a full stack application to be able to manage depression/anxiety and overall Mental well-being very effectively.

Keywords: mental health, mobile application, flutter, firebase, Depression, Anxiety

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Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: attention-based fully convolutional network, optic disc detection and segmentation, retinal fundus image, screening of ocular diseases

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Authors: Nalanda Matia, Julia Zhao, Amber Jaycocks, Divya Sinha

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Social assistance programs for businesses are intended to improve their survival and growth in the face of catastrophic events like the COVID-19 pandemic. However, that goal remains unfulfilled when the mostwantingbusinesses fail to participate in such programs. Reasons for non-participation can include lack of information, inability to cope with applications and program compliance, as well as some programs’ non-entitlement status. Some of these factors may be associated with the organizational and locational characteristics of these businesses. This research investigates these organizational and locational factorsthat determine receipt and effectiveness of social assistance among the firms that receive it. of A sample of firms from the universe of 3 rounds of Small Business Administration backed Paycheck Protection Program recipient and similarly profiled non recipient businesses are used to analyze this question. Initial results show firm organizational factors like size and spatial factors like broadband coverage at firm location impact application for and subsequent receipt of assistance for digitally administered programs. Further, Line of business and wage structure of recipients’ impact effectiveness of the assistance dollars.

Keywords: public economics, economics of social assistance, firm organizational structure, survival analysis

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Authors: Khandoker Upama Kabir, Mohammad Fuhad Anwar Sinha

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Dhaka, the capital of Bangladesh, is known not only for its fast growing economy, lively atmosphere, rich history, and culture but is also known for having a reputation of being a vastly populated city. The historic city centre of Dhaka (currently known as Puran Dhaka or Old Dhaka) which was conceived around the Pre-Mughal era and holds a lot of history and heritage of the region. This historic site has further been neglected, and most of the urban development has been done without integrating this part of the city into the plans. As a result, the festivals that take place traditionally throughout the year in this area create a greater impact on the urban fabric of the whole city. These festivals generate a huge amount of visitors and play a huge role in shaping the identity of the people. This paper will attempt to look at the importance of these traditions, the way these festivals are influencing the urban life of the community, and whether or not it has any significant effect on the economy. Through the use of both primary and secondary sources and SWOT analysis, this paper will attempt to identify the issues faced during these festivals. This paper will also try to suggest some basic remedies based on general comparisons between case studies of similar festivals celebrated globally and how these countries are dealing with such issues while also promoting tourism.

Keywords: urban fabric, festivals, cultural celebration, impact, historic city centre urban memory, mega events

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Authors: Sharad Singh, Ajay Kumar Sinha

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Coupled dampers like viscoelastic-frictional dampers for supplemental damping are a newer technique. In this paper, innovative Visco-frictional damping models have been presented and investigated. This paper attempts to couple frictional and fluid viscous dampers into a single unit of supplemental dampers. Visco-frictional damping model is developed by series and parallel coupling of frictional and fluid viscous dampers using Maxwell and Kelvin-Voigat models. The time analysis has been performed using numerical simulation on an SDOF system with varying fundamental periods, subject to a set of 12 ground motions. The simulation was performed using the direct time integration method. MATLAB programming tool was used to carry out the numerical simulation. The response behavior has been analyzed for the varying time period and added damping. This paper compares the response reduction behavior of the two modes of coupling. This paper highlights the performance efficiency of the suggested damping models. It also presents a mathematical modeling approach to visco-frictional dampers and simultaneously suggests the suitable mode of coupling between the two sub-units.

Keywords: hysteretic damping, Kelvin model, Maxwell model, parallel coupling, series coupling, viscous damping

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Authors: Ming-Yeh Lu, Shiao-Shing Chen, Saikat Sinha Ray, Hung-Te Hsu

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The submerged anaerobic osmotic membrane bioreactor (AnOMBR) integrated with periodic microfiltration (MF) extraction for simultaneous phosphorus and clean water recovery from wastewater was evaluated. A laboratory-scale AnOMBR used cellulose triacetate (CTA) membranes with effective membrane area of 130 cm² was fully submerged into a 5 L bioreactor at 30-35 ℃. Active layer was orientated to feed stream for minimizing membrane fouling and scaling. Additionally, a peristaltic pump was used to circulate magnesium sulphate (MgSO₄) solution applied as draw solution (DS). Microfiltration membrane periodically extracted about 1 L solution when the TDS reaches to 5 g/L to recover phosphorus and simultaneously control the salt accumulation in the bioreactor. During experiment progress, the average water flux was around 1.6 LMH. The AnOMBR process showed greater than 95% removal of soluble chemical oxygen demand (sCOD), nearly 100% of total phosphorous whereas only partial of ammonia was removed. On the other hand, the average methane production of 0.22 L/g sCOD was obtained. Subsequently, the overall performance demonstrates that a novel submerged AnOMBR system is potential for simultaneous wastewater treatment and resource recovery from wastewater. Therefore, the new concept of this system can be used to replace for the conventional AnMBR in the future.

Keywords: anaerobic treatment, forward osmosis, phosphorus recovery, membrane bioreactor

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Authors: Jain Jyoti, Jain Shorab, Sinha Shishir

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In the current scenario, development of new biodegradable composites with the reinforcement of some plant derived natural fibers are in major research concern. Abundant quantity of these natural plant derived fibers including sisal, ramp, jute, wheat straw, pine, pineapple, bagasse, etc. can be used exclusively or in combination with other natural or synthetic fibers to augment their specific properties like chemical, mechanical or thermal properties. Among all natural fibers, wheat straw, bagasse, kenaf, pineapple leaf, banana, coir, ramie, flax, etc. pineapple leaf fibers have very good mechanical properties. Being hydrophilic in nature, pineapple leaf fibers have very less affinity towards all types of polymer matrixes. Not much work has been carried out in this area. Surface treatments like alkaline treatment in different concentrations were conducted to improve its compatibility towards hydrophobic polymer matrix. Pineapple leaf fiber epoxy composites have been prepared using hand layup method. Effect of variation in fiber loading up to 20% in epoxy composites has been studied for mechanical properties like tensile strength and flexural strength. Analysis of fiber morphology has also been studied using FTIR, XRD. SEM micrographs have also been studied for fracture surface.

Keywords: composite, mechanical, natural fiber, pineapple leaf fiber

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan

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We perform an investigation of the unclosed terms in the evolution equation of the velocity gradient tensor (VGT) in compressible decaying turbulent flow. Velocity gradients in a compressible turbulent flow field influence several important nonlinear turbulent processes like cascading and intermittency. In an attempt to understand the dynamics of the velocity gradients various researchers have tried to model the unclosed terms in the evolution equation of the VGT. The existing models proposed for these unclosed terms have limited applicability. This is mainly attributable to the complex structure of the higher order gradient terms appearing in the evolution equation of VGT. We investigate these higher order gradients using the data from direct numerical simulation (DNS) of compressible decaying isotropic turbulent flow. The gas kinetic method aided with weighted essentially non-oscillatory scheme (WENO) based flow- reconstruction is employed to generate DNS data. By applying neural-network to the DNS data, we map the structure of the unclosed higher order gradient terms in the evolution of the equation of the VGT with VGT itself. We validate our findings by performing alignment based study of the unclosed higher order gradient terms obtained using the neural network with the strain rate eigenvectors.

Keywords: compressible turbulence, neural network, velocity gradient tensor, direct numerical simulation

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Authors: Alisha Sinha, Laxmi Kant Sharma

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Forest fires are a recurring issue in many parts of the world, including India. These fires can have various causes, including human activities (such as agricultural burning, campfires, or discarded cigarettes) and natural factors (such as lightning). This study presents a comprehensive and advanced methodology for assessing wildfire susceptibility by integrating diverse environmental variables and leveraging cutting-edge machine learning techniques across Rajasthan, India. The primary goal of the study is to utilize Google Earth Engine to compare locations in Sariska National Park, Rajasthan (India), before and after forest fires. High-resolution satellite data were used to assess the amount and types of changes caused by forest fires. The present study meticulously analyzes various environmental variables, i.e., slope orientation, elevation, normalized difference vegetation index (NDVI), drainage density, precipitation, and temperature, to understand landscape characteristics and assess wildfire susceptibility. In addition, a sophisticated random forest regression model is used to predict land surface temperature based on a set of environmental parameters.

Keywords: wildfire susceptibility mapping, LST, random forest, GEE, MODIS, climatic parameters

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Sanath Kumar Shetty, Sanya Sinha, K. Kamalakanth Shenoy

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The posterior reference for the ala tragal line is a cause of confusion, with different authors suggesting different locations as to the superior, middle or inferior part of the tragus. This study was conducted on 200 subjects to evaluate if any correlation exists between the variation of angulation of palatal throat form and the relative parallelism of occlusal plane to ala-tragal line at different tragal levels. A Custom made Occlusal Plane Analyzer was used to check the parallelism between the ala-tragal line and occlusal plane. A lateral cephalogram was shot for each subject to measure the angulation of the palatal throat form. Fisher’s exact test was used to evaluate the correlation between the angulation of the palatal throat form and the relative parallelism of occlusal plane to the ala tragal line. Also, a classification was formulated for the palatal throat form, based on confidence interval. From the results of the study, the inferior part, middle part and superior part of the tragus were seen as the reference points in 49.5%, 32% and 18.5% of the subjects respectively. Class I palatal throat form (41degree-50 degree), Class II palatal throat form (below 41 degree) and Class III palatal throat form (above 50 degree) were seen in 42%, 43% and 15% of the subjects respectively. It was also concluded that there is no significant correlation between the variation in the angulations of the palatal throat form and the relative parallelism of occlusal plane to the ala-tragal line.

Keywords: Ala-Tragal line, occlusal plane, palatal throat form, cephalometry

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Authors: Saurabh Chaudhury, Sanjeet Kumar Sinha

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The MOSFET has been the main building block in high performance and low power VLSI chips for the last several decades. Device scaling is fundamental to technological advancements, which allows more devices to be integrated on a single die providing greater functionality per chip. Ultimately, the goal of scaling is to build an individual transistor that is smaller, faster, cheaper, and consumes less power. Scaling continued following Moore's law initially and now we see an exponential growth in today's nano scaled chip. However, device scaling to deep nano meter regime leads to exponential increase in leakage currents and excessive heat generation. Moreover, fabrication process variability causing a limitation to further scaling. Researchers believe that with a mix of chemistry, physics, and engineering, nano electronics may provide a solution to increasing fabrication costs and may allow integrated circuits to be scaled beyond the limits of the modern transistor. Carbon nano tube (CNT) and nano wires (NW) based FETs have been analyzed and characterized in laboratory and also been demonstrated as prototypes. This work presents an extensive simulation based study and analysis of CNTFET and NW-FET devices and comparison of the results with conventional MOSFET. From this study, we can conclude that these devices have got some excellent properties and favorable characteristics which will definitely lead the future semiconductor devices in post silicon era.

Keywords: carbon nanotube, nanowire FET, low power, nanoscaled devices, VLSI

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Authors: Sujit Kumar Sinha, R. Chattopadhyay

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In the course of processing phases and use, fibres, yarns, or fabrics are subjected to a variety of stresses and strains, which cause the development of internal stresses. Given an opportunity, these inherent stresses try to bring back the structure to the original state. As an example, a twisted yarn always shows a tendency to untwist whenever its one end is made free. If the yarn is not held under tension, it may form snarls due to the presence of excessive torque. The running performance of such yarn or thread may, therefore, get negatively affected by it, as a snarl may not pass through the knitting or sewing needle smoothly, leading to an end break. A fabric shows a tendency to form wrinkles whenever squeezed. It may also shrink when brought to a relaxed state. In order to improve performance (i.e., dimensional stability or appearance), stabilization of the structure is needed. The stabilization can be attained through the release of internal stresses, which can be brought about by the process of annealing and/or other finishing treatments. When a fabric is subjected to heat, a change in the properties of the fibers, yarns, and fabric is expected. The degree to which the properties are affected would depend upon the condition of heat treatment and on the properties & structure of fibres, yarns, and fabric. In the present study, an attempt has been made to investigate the effect of annealing treatment on the properties of polyester cotton yarns with varying sheath structures.

Keywords: friction spun yarn, annealing, tenacity, structural integrity, decay

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Authors: Sarthak Mishra, Astha Sinha

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There’s no doubt about the convenience of making commercial and business transactions over the Internet under the new business model known as the e-Commerce. The term 'Electronic commerce' or e-Commerce refers to the use of an electronic medium to carry out commercial transactions. E-Commerce is one of the parts of Information Science framework and its uses are gradually becoming popular. Thus, the threat of security issues in Information Science has now become an important subject of discussion amongst the concerned users. These two issues i.e. security and privacy are required to be looked into through social, organizational, technical and economic perspectives. The current paper analyses the effect of these two issues in the arena of e-commerce. Here, no specification has been discussed rather an attempt has been made to provide a general overview. Further, attempts have been made to discuss the security and privacy issues in relation to the E-Commerce financial transactions. We shall also discuss in particular different steps required to be taken before online shopping and also shall discuss the purpose of security and privacy in E-Commerce and why it has currently become the need of the present hour. Lastly, an attempt has been made to discuss the plausible future course of development of this practice and its impact upon the global economy and if any changes should be bought about to ensure a smooth evolution of the practice. This paper has adopted a descriptive methodology to undertake its major area of study, wherein the major source of information has been via the secondary resources. Also, the study is of a comparative nature wherein the position of the various national regimes have compared with regards to the research question.

Keywords: business-business transaction (B2B), business-consumer transaction (B2C), e-commerce, online transaction, privacy and security threats

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Authors: Vidishaa Jali, Amit Sinha, Kameshwar Prasad

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Background and Objective: Cerebral microbleeds are frequently found in healthy elderly individuals. We performed a meta- analysis to determine the prevalence of cerebral microbleeds in apparently healthy, elderly population and to determine the effect of age, smoking and hypertension on the occurrence of cerebral microbleeds. Methods: Relevant literature was searched using electronic databases such as MEDLINE, EMBASE, PubMed, Cochrane database, Google scholar to identify studies on the prevalence of cerebral microbleeds in general elderly population till March 2016. STATA version 13 software was used for analysis. Fixed effect model was used if heterogeneity was less than 50%. Otherwise, random effect model was used. Meta- regression analysis was performed to check any effect of important variables such as age, smoking, hypertension. Selection Criteria: We included cross-sectional studies performed in apparently healthy elderly population, who had age more than 50 years. Results: The pooled proportion of cerebral microbleeds in healthy population is 12% (95% CI, 0.11 to 0.13). No significant effect of age was found on the prevalence of cerebral microbleeds (p= 0.99). A linear relationship between increase in hypertension and the prevalence of cerebral microbleeds was found, however, this linear relationship was not statistically significant (p=0.16). Similarly, A linear relationship between increase in smoking and the prevalence of cerebral microbleeds was found, however, this linear relationship was also not statistically significant (p=0.21). Conclusion: Presence of cerebral microbleeds is evident in apparently healthy, elderly population, in more than 10% of individuals.

Keywords: apparently healthy, elderly, prevalence, cerebral microbleeds

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Authors: Gaurav Kumar Sinha

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The oil and gas industry, characterized by its complex and global supply chains, faces significant challenges in ensuring security, transparency, and efficiency. Blockchain technology, with its decentralized and immutable ledger, offers a transformative solution to these issues. This paper explores the application of blockchain technology in the oil and gas supply chain, highlighting its potential to enhance data security, improve transparency, and streamline operations. By leveraging smart contracts, blockchain can automate and secure transactions, reducing the risk of fraud and errors. Additionally, the integration of blockchain with IoT devices enables real-time tracking and monitoring of assets, ensuring data accuracy and integrity throughout the supply chain. Case studies and pilot projects within the industry demonstrate the practical benefits and challenges of implementing blockchain solutions. The findings suggest that blockchain technology can significantly improve trust and collaboration among supply chain participants, ultimately leading to more efficient and resilient operations. This study provides valuable insights for industry stakeholders considering the adoption of blockchain technology to address their supply chain management challenges.

Keywords: blockchain technology, oil and gas supply chain, data security, transparency, smart contracts, IoT integration, real-time tracking, asset monitoring, fraud reduction, supply chain efficiency, data integrity, case studies, industry implementation, trust, collaboration.

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Authors: Ramesh Kumar, Rajesh Kumar, Shaktiman Singh, Atar Singh, Anshuman Bhardwaj, Ravindra Kumar Sinha, Anupma Kumari

Abstract:

A detailed study of the ion chemistry of the Shaune Garnag glacier meltwater has been carried out to assess the role of active glacier in the chemical denudation rate. The chemical compositions of various ions in meltwater of the Shaune Garang glacier were analyzed during the melting period 2015 and 2016. Total 112 of melt water samples twice in a day were collected during ablation season of 2015 and 2016. To identify various factors controlling the dissolved ionic strength of Shaune Garang Glacier meltwater statistical analysis such as correlation matrix, Principle Component Analysis (PCA) and factor analysis were applied to deduce the result. Cation concentration for Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ in the meltwater for both the years can be arranged in the order as Ca²⁺ > Mg²⁺ > Na⁺ > K⁺. Study showed that Ca²⁺ and HCO₃⁻ found to be dominant on the both melting period. Carbonate weathering identified as the dominant process controlling the dissolved ion chemistry of meltwater due to the high ratios of (Ca²⁺ + Mg²⁺) versus TZ+ and (Ca²⁺ + Mg²⁺) versus (Na⁺ + K⁺) in the study area. The cation denudation rate of the Shaune Garnag catchment is 3412.2 m⁻² a⁻¹, i.e. higher than the other glacierised catchment in the Himalaya, indicating intense chemical erosion in this catchment.

Keywords: Shaune Garang glacier, Hydrochemistry, chemical composition, cation denudation rate, carbonate weathering

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Authors: Srishti Sinha, Deepti Tikariha, Kallol K. Ghosh

Abstract:

Over the past few decades protein-surfactant interactions have been a subject of extensive studies as they are of great importance in wide variety of industries, biological, pharmaceutical and cosmetic systems. Protein-surfactant interactions have been explored the effect of surfactants on structure of protein in the form of solubilization and denaturing or renaturing of protein. Globular proteins are frequently used as functional ingredients in healthcare and pharmaceutical products, due to their ability to catalyze biochemical reactions, to be adsorbed on the surface of some substance and to bind other moieties and form molecular aggregates. One of the most widely used globular protein is bovine serum albumin (BSA), since it has a well-known primary structure and been associated with the binding of many different categories of molecules, such as dyes, drugs and toxic chemicals. Protein−surfactant interactions are usually dependent on the surfactant features. Most of the research has been focused on single-chain surfactants. More recently, the binding between proteins and dimeric surfactants has been discussed. In present study interactions of one dimeric surfactant Butanediyl-1,4-bis (dimethylhexadecylammonium bromide) (16-4-16, 2Br-) and the corresponding single-chain surfactant cetyl trimethylammonium bromide (CTAB) with bovine serum albumin (BSA) have been investigated by surface tension and spectrofluoremetric methods. It has been found that the bindings of all gemini surfactant to BSA were cooperatively driven by electrostatic and hydrophobic interactions. The gemini surfactant carrying more charges and hydrophobic tails, showed stronger interactions with BSA than the single-chain surfactant.

Keywords: bovine serum albumin, gemini surfactants, hydrophobic interactions, protein surfactant interaction

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Authors: Vibha Sinha, Sumedha Chakma

Abstract:

Arsenic (As) contamination in drinking water is a serious concern worldwide resulting in severe health maladies. To tackle this problem, several hydrogel based matrix which selectively uptake toxic metals from contaminated water has increasingly been examined as a potential practical method for metal removal. The major concern in hydrogels is low stability of matrix, resulting in poor performance. In this study, the potential of hybrid hydrogel-biochar matrix synthesized from natural plant polymers, specific for As removal was explored. Various compositional and functional group changes of the elements contained in the matrix due to the adsorption of As were identified. Moreover, to resolve the stability issue in hydrogel matrix, optimum and effective mixing of hydrogel with biochar was studied. Mixing varied proportions of matrix components at the time of digestion process was tested. Preliminary results suggest that partial premixing methods may increase the stability and reduce cost. Addition of nanoparticles and specific catalysts with different concentrations of As(III) and As(V) under batch conditions was performed to study their role in performance enhancement of the hydrogel matrix. Further, effect of process parameters, optimal uptake conditions and detailed mechanism derived from experimental studies were suitably conducted. This study provides an efficient, specific and a low-cost As removal method that offers excellent regeneration abilities which can be reused for value.

Keywords: arsenic, catalysts, hybrid hydrogel-biochar, water purification

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Authors: Jain Jyoti, Jain Shorab, Sinha Shishir

Abstract:

In the field of material engineering, composites are in great concern for their nonbiodegradability and their cost. In order to reduce its cost and weight, plant derived fibers witnessed miraculous triumph. Plant fibers can be of different types like seed fibers, blast fibers, leaf fibers, etc. Composites can be reinforced with exclusively one type of natural fiber or also can be combined with two or more different types of natural or synthetic fibers to boost up their specific properties. Among all natural fibers, wheat straw, bagasse, kenaf, pineapple leaf, banana, coir, ramie, flax, etc. pineapple leaf fibers have very good mechanical properties. Being hydrophilic in nature, pineapple leaf fibers have very less affinity towards all types of polymer matrixes like HDPE, LDPE, PET, epoxy, etc. Surface treatments like alkaline treatment in different concentrations were conducted to improve its adhesion and compatibility towards hydrophobic polymer matrix i.e. epoxy resin. Pineapple leaf fiber epoxy composites have been prepared using hand layup method. Effect of fiber loading and surface treatments have been studied for different mechanical properties i.e. tensile strength, flexural strength and impact properties of pineapple leaf fiber composites. Analysis of fiber morphology has also been studied using FTIR, XRD. Scanning electron microscopy has also been used to study and compare the morphology of untreated and treated fibers. Also, the fracture surface has been reviewed comparing the reported literature of other eminent researchers of this field.

Keywords: composite, mechanical, natural fiber, pineapple leaf fiber

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

Abstract:

Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 153