Search results for: Anup Gupta
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 400

Search results for: Anup Gupta

340 Load Balancing Algorithms for SIP Server Clusters in Cloud Computing

Authors: Tanmay Raj, Vedika Gupta

Abstract:

For its groundbreaking and substantial power, cloud computing is today’s most popular breakthrough. It is a sort of Internet-based computing that allows users to request and receive numerous services in a cost-effective manner. Virtualization, grid computing, and utility computing are the most widely employed emerging technologies in cloud computing, making it the most powerful. However, cloud computing still has a number of key challenges, such as security, load balancing, and non-critical failure adaption, to name a few. The massive growth of cloud computing will put an undue strain on servers. As a result, network performance will deteriorate. A good load balancing adjustment can make cloud computing more productive and in- crease client fulfillment execution. Load balancing is an important part of cloud computing because it prevents certain nodes from being overwhelmed while others are idle or have little work to perform. Response time, cost, throughput, performance, and resource usage are all parameters that may be improved using load balancing.

Keywords: cloud computing, load balancing, computing, SIP server clusters

Procedia PDF Downloads 87
339 Wavelength Conversion of Dispersion Managed Solitons at 100 Gbps through Semiconductor Optical Amplifier

Authors: Kadam Bhambri, Neena Gupta

Abstract:

All optical wavelength conversion is essential in present day optical networks for transparent interoperability, contention resolution, and wavelength routing. The incorporation of all optical wavelength convertors leads to better utilization of the network resources and hence improves the efficiency of optical networks. Wavelength convertors that can work with Dispersion Managed (DM) solitons are attractive due to their superior transmission capabilities. In this paper, wavelength conversion for dispersion managed soliton signals was demonstrated at 100 Gbps through semiconductor optical amplifier and an optical filter. The wavelength conversion was achieved for a 1550 nm input signal to1555nm output signal. The output signal was measured in terms of BER, Q factor and system margin.    

Keywords: all optical wavelength conversion, dispersion managed solitons, semiconductor optical amplifier, cross gain modultation

Procedia PDF Downloads 420
338 Emotion-Convolutional Neural Network for Perceiving Stress from Audio Signals: A Brain Chemistry Approach

Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

Abstract:

Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

Procedia PDF Downloads 124
337 Performance Evaluation of One and Two Dimensional Prime Codes for Optical Code Division Multiple Access Systems

Authors: Gurjit Kaur, Neena Gupta

Abstract:

In this paper, we have analyzed and compared the performance of various coding schemes. The basic ID prime sequence codes are unique in only dimension, i.e. time slots, whereas 2D coding techniques are not unique by their time slots but with their wavelengths also. In this research, we have evaluated and compared the performance of 1D and 2D coding techniques constructed using prime sequence coding pattern for Optical Code Division Multiple Access (OCDMA) system on a single platform. Analysis shows that 2D prime code supports lesser number of active users than 1D codes, but they are having large code family and are the most secure codes compared to other codes. The performance of all these codes is analyzed on basis of number of active users supported at a Bit Error Rate (BER) of 10-9.

Keywords: CDMA, OCDMA, BER, OOC, PC, EPC, MPC, 2-D PC/PC, λc, λa

Procedia PDF Downloads 310
336 A Case Study Demonstrating the Benefits of Low-Carb Eating in an Adult with Latent Autoimmune Diabetes Highlights the Necessity and Effectiveness of These Dietary Therapies

Authors: Jasmeet Kaur, Anup Singh, Shashikant Iyengar, Arun Kumar, Ira Sahay

Abstract:

Latent autoimmune diabetes in adults (LADA) is an irreversible autoimmune disease that affects insulin production. LADA is characterized by the production of Glutamic acid decarboxylase (GAD) antibodies, which is similar to type 1 diabetes. Individuals with LADA may eventually develop overt diabetes and require insulin. In this condition, the pancreas produces little or no insulin, which is a hormone used by the body to allow glucose to enter cells and produce energy. While type 1 diabetes was traditionally associated with children and teenagers, its prevalence has increased in adults as well. LADA is frequently misdiagnosed as type 2 diabetes, especially in adulthood when type 2 diabetes is more common. LADA develops in adulthood, usually after age 30. Managing LADA involves metabolic control with exogenous insulin and prolonging the life of surviving beta cells, thereby slowing the disease's progression. This case study examines the impact of approximately 3 months of low-carbohydrate dietary intervention in a 42-year-old woman with LADA who was initially misdiagnosed as having type 2 diabetes. Her c-peptide was 0.13 and her HbA1c was 9.3% when this trial began. Low-carbohydrate interventions have been shown to improve blood sugar levels, including fasting, post-meal, and random blood sugar levels, as well as haemoglobin levels, blood pressure, energy levels, sleep quality, and satiety levels. The use of low-carbohydrate dietary intervention significantly reduces both hypo- and hyperglycaemia events. During the 3 months of the study, there were 2 to 3 hyperglycaemic events owing to physical stress and a single hypoglycaemic event. Low-carbohydrate dietary therapies lessen insulin dose inaccuracy, which explains why there were fewer hyperglycaemic and hypoglycaemic events. In three months, the glycated haemoglobin (HbA1c) level was reduced from 9.3% to 6.3%. These improvements occur without the need for caloric restriction or physical activity. Stress management was crucial aspect of the treatment plan as stress-induced neuroendocrine hormones can cause immunological dysregulation. Additionally, supplements that support immune system and reduce inflammation were used as part of the treatment during the trial. Long-term studies are needed to track disease development and corroborate the claim that such dietary treatments can prolong the honeymoon phase in LADA. Various factors can contribute to additional autoimmune attacks, so measuring c-peptide is crucial on a regular basis to determine whether insulin levels need to be adjusted.

Keywords: autoimmune, diabetes, LADA, low_carb, nutrition

Procedia PDF Downloads 8
335 Sensitivity and Uncertainty Analysis of Hydrocarbon-In-Place in Sandstone Reservoir Modeling: A Case Study

Authors: Nejoud Alostad, Anup Bora, Prashant Dhote

Abstract:

Kuwait Oil Company (KOC) has been producing from its major reservoirs that are well defined and highly productive and of superior reservoir quality. These reservoirs are maturing and priority is shifting towards difficult reservoir to meet future production requirements. This paper discusses the results of the detailed integrated study for one of the satellite complex field discovered in the early 1960s. Following acquisition of new 3D seismic data in 1998 and re-processing work in the year 2006, an integrated G&G study was undertaken to review Lower Cretaceous prospectivity of this reservoir. Nine wells have been drilled in the area, till date with only three wells showing hydrocarbons in two formations. The average oil density is around 300API (American Petroleum Institute), and average porosity and water saturation of the reservoir is about 23% and 26%, respectively. The area is dissected by a number of NW-SE trending faults. Structurally, the area consists of horsts and grabens bounded by these faults and hence compartmentalized. The Wara/Burgan formation consists of discrete, dirty sands with clean channel sand complexes. There is a dramatic change in Upper Wara distributary channel facies, and reservoir quality of Wara and Burgan section varies with change of facies over the area. So predicting reservoir facies and its quality out of sparse well data is a major challenge for delineating the prospective area. To characterize the reservoir of Wara/Burgan formation, an integrated workflow involving seismic, well, petro-physical, reservoir and production engineering data has been used. Porosity and water saturation models are prepared and analyzed to predict reservoir quality of Wara and Burgan 3rd sand upper reservoirs. Subsequently, boundary conditions are defined for reservoir and non-reservoir facies by integrating facies, porosity and water saturation. Based on the detailed analyses of volumetric parameters, potential volumes of stock-tank oil initially in place (STOIIP) and gas initially in place (GIIP) were documented after running several probablistic sensitivity analysis using Montecalro simulation method. Sensitivity analysis on probabilistic models of reservoir horizons, petro-physical properties, and oil-water contacts and their effect on reserve clearly shows some alteration in the reservoir geometry. All these parameters have significant effect on the oil in place. This study has helped to identify uncertainty and risks of this prospect particularly and company is planning to develop this area with drilling of new wells.

Keywords: original oil-in-place, sensitivity, uncertainty, sandstone, reservoir modeling, Monte-Carlo simulation

Procedia PDF Downloads 172
334 Civil Nuclear Liability Indian Perspective

Authors: Shivani Gupta, Shrishti Chaturvedi

Abstract:

By using a miniscule of nuclear matter, the problem of immeasurable human needs for energy can be resolved. However since nuclear energy also has the inherent potential for catastrophic destruction, one should be extremely mindful of the consequences should a mischance occur. Civil Nuclear Liability has recently gained a lot of momentum after India entered into agreements with nations like United States of America, France and others. Also now India is a part of the Convention on Supplementary Compensation (CSC). With a history of Bhopal Gas Tragedy, India is now much more vigilant about the latest developments in this sector. Therefore, it has become imperative to analyses the liability regime in the background of international conventions such as Vienna Convention 1963, Paris Convention 1960, Convention on Supplementary Compensation, 1997 and others. Also the present Indian legal scenarios in this regard which are derived from Civil Liability for Nuclear Damages Act, 2010 and Civil Liability for Nuclear Damages Rules, 2011 have also been extensively discussed in the paper.

Keywords: nuclear liability, civil liability for nuclear damages act, 2010, civil liability for nuclear damages rules, India

Procedia PDF Downloads 377
333 Overview of Time, Resource and Cost Planning Techniques in Construction Management Research

Authors: R. Gupta, P. Jain, S. Das

Abstract:

One way to approach construction scheduling optimization problem is to focus on the individual aspects of planning, which can be broadly classified as time scheduling, crew and resource management, and cost control. During the last four decades, construction planning has seen a lot of research, but to date, no paper had attempted to summarize the literature available under important heads. This paper addresses each of aspects separately, and presents the findings of an in-depth literature of the various planning techniques. For techniques dealing with time scheduling, the authors have adopted a rough chronological documentation. For crew and resource management, classification has been done on the basis of the different steps involved in the resource planning process. For cost control, techniques dealing with both estimation of costs and the subsequent optimization of costs have been dealt with separately.

Keywords: construction planning techniques, time scheduling, resource planning, cost control

Procedia PDF Downloads 453
332 CO2 Sequestration for Enhanced Coal Bed Methane Recovery: A New Approach

Authors: Abhinav Sirvaiya, Karan Gupta, Pankaj Garg

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The global warming due to the increased atmospheric carbon dioxide (CO2) concentration is the most prominent issue of environment that the world is facing today. To solve this problem at global level, sequestration of CO2 in deep and unmineable coal seams has come out as one of the attractive alternatives to reduce concentration in atmosphere. This sequestration technology is not only going to help in storage of CO2 beneath the sub-surface but is also playing a major role in enhancing the coal bed methane recovery (ECBM) by displacing the adsorbed methane. This paper provides the answers for the need of CO2 injection in coal seams and how recovery is enhanced. We have discussed the recent development in enhancing the coal bed methane recovery and the economic scenario of the same. The effect of injection on the coal reservoir has also been discussed. Coal is a good absorber of CO2. That is why the sequestration of CO2 is emerged out to be a great approach, not only for storage purpose but also for enhancing coal bed methane recovery.

Keywords: global warming, carbon dioxide (CO2), CO2 sequestration, enhance coal bed methane (ECBM)

Procedia PDF Downloads 471
331 Dissolved Gas Analysis Based Regression Rules from Trained ANN for Transformer Fault Diagnosis

Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

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Dissolved Gas Analysis (DGA) has been widely used for fault diagnosis in a transformer. Artificial neural networks (ANN) have high accuracy but are regarded as black boxes that are difficult to interpret. For many problems it is desired to extract knowledge from trained neural networks (NN) so that the user can gain a better understanding of the solution arrived by the NN. This paper applies a pedagogical approach for rule extraction from function approximating neural networks (REFANN) with application to incipient fault diagnosis using the concentrations of the dissolved gases within the transformer oil, as the input to the NN. The input space is split into subregions and for each subregion there is a linear equation that is used to predict the type of fault developing within a transformer. The experiments on real data indicate that the approach used can extract simple and useful rules and give fault predictions that match the actual fault and are at times also better than those predicted by the IEC method.

Keywords: artificial neural networks, dissolved gas analysis, rules extraction, transformer

Procedia PDF Downloads 495
330 Piezo-Extracted Model Based Chloride/ Carbonation Induced Corrosion Assessment in Reinforced Concrete Structures

Authors: Gupta. Ashok, V. talakokula, S. bhalla

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Rebar corrosion is one of the main causes of damage and premature failure of the reinforced concrete (RC) structures worldwide, causing enormous costs for inspection, maintenance, restoration and replacement. Therefore, early detection of corrosion and timely remedial action on the affected portion can facilitate an optimum utilization of the structure, imparting longevity to it. The recent advent of the electro-mechanical impedance (EMI) technique using piezo sensors (PZT) for structural health monitoring (SHM) has provided a new paradigm to the maintenance engineers to diagnose the onset of the damage at the incipient stage itself. This paper presents a model based approach for corrosion assessment based on the equivalent parameters extracted from the impedance spectrum of concrete-rebar system using the EMI technique via the PZT sensors.

Keywords: impedance, electro-mechanical, stiffness, mass, damping, equivalent parameters

Procedia PDF Downloads 513
329 Early Stage Suicide Ideation Detection Using Supervised Machine Learning and Neural Network Classifier

Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

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In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

Procedia PDF Downloads 62
328 GPS Devices to Increase Efficiency of Indian Auto-Rickshaw Segment

Authors: Sanchay Vaidya, Sourabh Gupta, Gouresh Singhal

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There are various modes of transport in metro cities in India, auto-rickshaws being one of them. Auto-rickshaws provide connectivity to all the places in the city offering last mile connectivity. Among all the modes of transport, the auto-rickshaw industry is the most unorganized and inefficient. Although unions exist in different cities they aren’t good enough to cope up with the upcoming advancements in the field of technology. An introduction of simple technology in this field may do wonder and help increase the revenues. This paper aims to organize this segment under a single umbrella using GPS devices and mobile phones. The paper includes surveys of about 300 auto-rickshaw drivers and 1000 plus commuters across 6 metro cities in India. Carrying out research and analysis provides a base for the development of this model and implementation of this innovative technique, which is discussed in this paper in detail with ample emphasis given on the implementation of this model.

Keywords: auto-rickshaws, business model, GPS device, mobile application

Procedia PDF Downloads 204
327 Avoiding Packet Drop for Improved through Put in the Multi-Hop Wireless N/W

Authors: Manish Kumar Rajak, Sanjay Gupta

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Mobile ad hoc networks (MANETs) are infrastructure less and intercommunicate using single-hop and multi-hop paths. Network based congestion avoidance which involves managing the queues in the network devices is an integral part of any network. QoS: A set of service requirements that are met by the network while transferring a packet stream from a source to a destination. Especially in MANETs, packet loss results in increased overheads. This paper presents a new algorithm to avoid congestion using one or more queue on nodes and corresponding flow rate decided in advance for each node. When any node attains an initial value of queue then it sends this status to its downstream nodes which in turn uses the pre-decided flow rate of packet transfer to its upstream nodes. The flow rate on each node is adjusted according to the status received from its upstream nodes. This proposed algorithm uses the existing infrastructure to inform to other nodes about its current queue status.

Keywords: mesh networks, MANET, packet count, threshold, throughput

Procedia PDF Downloads 445
326 Modular Robotics and Terrain Detection Using Inertial Measurement Unit Sensor

Authors: Shubhakar Gupta, Dhruv Prakash, Apoorv Mehta

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In this project, we design a modular robot capable of using and switching between multiple methods of propulsion and classifying terrain, based on an Inertial Measurement Unit (IMU) input. We wanted to make a robot that is not only intelligent in its functioning but also versatile in its physical design. The advantage of a modular robot is that it can be designed to hold several movement-apparatuses, such as wheels, legs for a hexapod or a quadpod setup, propellers for underwater locomotion, and any other solution that may be needed. The robot takes roughness input from a gyroscope and an accelerometer in the IMU, and based on the terrain classification from an artificial neural network; it decides which method of propulsion would best optimize its movement. This provides the bot with adaptability over a set of terrains, which means it can optimize its locomotion on a terrain based on its roughness. A feature like this would be a great asset to have in autonomous exploration or research drones.

Keywords: modular robotics, terrain detection, terrain classification, neural network

Procedia PDF Downloads 108
325 Effects of Turbulence Penetration on Valve Leakage in Nuclear Reactor Coolant System

Authors: Gupta Rajesh, Paudel Sagar, Sharma Utkarsh, Singh Amit Kumar

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Thermal stratification has drawn much attention because of the malfunctions at various nuclear plants in U.S.A that raised significant safety concerns. The concerns due to this phenomenon relate to thermal stresses in branch pipes connected to the reactor coolant system piping. This stress limits the lifetime of the piping system, and even leading to penetrating cracks. To assess origin of valve damage in the pipeline, it is essential to determine the effect of turbulence penetration on valve leakage; since stratified flow is generally generated by turbulent penetration or valve leakage. As a result, we concluded with the help of coupled fluent-structural analysis that the pipe with less turbulence has less chance of failure there by requiring less maintenance.

Keywords: nuclear reactor coolant system, thermal stratification, turbulent penetration, coupled fluent-structural analysis, Von-Misses stress

Procedia PDF Downloads 257
324 Identification of Parameters for Urban and Regional Level Infrastructure Development - A Theoretical Perspective: Case Study – Rail Based Mass Transit in Indian Cities

Authors: Chitresh Kumar, Santanu Gupta

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The research work intends to understand the process of initiation, planning and development of capital-intensive urban area level infrastructure development in East Asian Cities (specific to Indian Cities). With the onset of emphasis on sustainable urban transport, self-financed urban local bodies, it has become of utmost important to identify infrastructure and projects on a priority basis, which provide optimal utility to the urban area. Through identification of Spatial, Demographic and Socio-Economic and Political Instability Parameters and their trends for the past 60 years at the urban area and state level, the paper attempts to identify the most suitable time period when initiation of the project would become economically and demographically viable for the city.

Keywords: urban planning, regional planning, mass transit, infrastructure development, spatial planning

Procedia PDF Downloads 528
323 Loss in Efficacy of Viscoelastic Ionic Liquid Surfactants under High Salinity during Surfactant Flooding

Authors: Shilpa K. Nandwani, Mousumi Chakraborty, Smita Gupta

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When selecting surfactants for surfactant flooding during enhanced oil recovery, the most important criteria is that the surfactant system should reduce the interfacial tension between water and oil to ultralow values. In the present study, a mixture of ionic liquid surfactant and commercially available binding agent sodium tosylate has been used as a surfactant mixture. Presence of wormlike micelles indicates the possibility of achieving ultralow interfacial tension. Surface tension measurements of the mixed surfactant system have been studied. The emulsion size distribution of the mixed surfactant system at varying salinities has been studied. It has been found that at high salinities the viscoelastic surfactant system loses their efficacy and degenerate. Hence the given system may find application in low salinity reservoirs, providing good mobility to the flood during tertiary oil recovery process.

Keywords: ionic liquis, interfacial tension, Na-tosylate, viscoelastic surfactants

Procedia PDF Downloads 224
322 Convergence Analysis of Cubic B-Spline Collocation Method for Time Dependent Parabolic Advection-Diffusion Equations

Authors: Bharti Gupta, V. K. Kukreja

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A comprehensive numerical study is presented for the solution of time-dependent advection diffusion problems by using cubic B-spline collocation method. The linear combination of cubic B-spline basis, taken as approximating function, is evaluated using the zeros of shifted Chebyshev polynomials as collocation points in each element to obtain the best approximation. A comparison, on the basis of efficiency and accuracy, with the previous techniques is made which confirms the superiority of the proposed method. An asymptotic convergence analysis of technique is also discussed, and the method is found to be of order two. The theoretical analysis is supported with suitable examples to show second order convergence of technique. Different numerical examples are simulated using MATLAB in which the 3-D graphical presentation has taken at different time steps as well as different domain of interest.

Keywords: cubic B-spline basis, spectral norms, shifted Chebyshev polynomials, collocation points, error estimates

Procedia PDF Downloads 193
321 Multi-Criteria Goal Programming Model for Sustainable Development of India

Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

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Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

Procedia PDF Downloads 195
320 Revised Technology Acceptance Model Framework for M-Commerce Adoption

Authors: Manish Gupta

Abstract:

Following the E-Commerce era, M-Commerce is the next big phase in the technology involvement and advancement. This paper intends to explore how Indian consumers are influenced to adopt the M-commerce. In this paper, the revised Technology Acceptance Model (TAM) has been presented on the basis of the most dominant factors that affect the adoption of M-Commerce in Indian scenario. Furthermore, an analytical questionnaire approach was carried out to collect data from Indian consumers. These collected data were further used for the validation of the presented model. Findings indicate that customization, convenience, instant connectivity, compatibility, security, download speed in M-Commerce affect the adoption behavior. Furthermore, the findings suggest that perceived usefulness and attitude towards M-Commerce are positively influenced by number of M-Commerce drivers (i.e. download speed, compatibility, convenience, security, customization, connectivity, and input mechanism).

Keywords: M-Commerce, perceived usefulness, technology acceptance model, perceived ease of use

Procedia PDF Downloads 274
319 Innate Immune Expression in Heterophils in Response to LPS

Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

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Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover, this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

Procedia PDF Downloads 468
318 Enhancing the Efficiency of Organic Solar Cells Using Metallic Nanoparticles

Authors: Sankara Rao Gollu, Ramakant Sharma, G. Srinivas, Souvik Kundu, Dipti Gupta

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In recent years, bulk heterojunction organic solar cells (BHJ OSCs) based on polymer–fullerene attracted a large research attention due to their numerous advantages such as light weight, easy processability, eco-friendly, low-cost, and capability for large area roll-to-roll manufacturing. BHJ OSCs usually suffer from insufficient light absorption due to restriction on keeping thin ( < 150 nm) photoactive layer because of small exciton diffusion length ( ~ 10 nm) and low charge carrier mobilities. It is thus highly desirable that light absorption as well as charge transport properties are enhanced by alternative methods so as to improve the device efficiency. In this work, therefore, we have focused on the strategy of incorporating metallic nanostructures in the active layer or charge transport layer to enhance the absorption and improve the charge transport.

Keywords: organic solar cell, efficiency, bulk heterojunction, polymer-fullerene

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317 Simultaneous Determination of Proposed Anti-HIV Combination Comprising of Elvitegravir and Quercetin in Rat Plasma Using the HPLC–ESI-MS/MS Method: Drug Interaction Study

Authors: Lubna Azmi, Ila Shukla, Shyam Sundar Gupta, Padam Kant, C. V. Rao

Abstract:

Elvitegravir is the mainstay of anti-HIV combination therapy in most endemic countries presently. However, it cannot be used alone owing to its long onset time of action. 2-(3,4-dihydroxyphenyl)-3,5,7-trihydroxychromen-4-one (Quercetin: QU) is a polyphenolic compound obtained from Argeria speciosa Linn (Family: Convolvulaceae), an anti-HIV candidate. In the present study, a sensitive, simple and rapid high-performance liquid chromatography coupled with positive ion electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) method was developed for the simultaneous determination elvitegravir and Quercetin, in rat plasma. The method was linear over a range of 0.2–500 ng/ml. All validation parameters met the acceptance criteria according to regulatory guidelines. LC–MS/MS method for determination of Elvitegravir and Quercetin was developed and validated. Results show the potential of drug–drug interaction upon co-administration this marketed drugs and plant derived secondary metabolite.

Keywords: anti-HIV resistance, extraction, HPLC-ESI-MS-MS, validation

Procedia PDF Downloads 315
316 Assessment of Highly Sensitive Dielectric Modulated GaN-FinFET for Label-Free Biosensing Applications

Authors: Ajay Kumar, Neha Gupta

Abstract:

This work presents the sensitivity assessment of Gallium Nitride (GaN) material-based FinFET by dielectric modulation in the nanocavity gap for label-free biosensing applications. The significant deflection is observed in the electrical characteristics such as drain current (ID), transconductance (gm), surface potential, energy band profile, electric field, sub-threshold slope (SS), and threshold voltage (Vth) in the presence of biomolecules owing to GaN material. Further, the device sensitivity is evaluated to identify the effectiveness of the proposed biosensor and its capability to detect the biomolecules with high precision or accuracy. Higher sensitivity is observed for Gelatin (k=12) in terms of on-current (SION), threshold voltage (SVth), and switching ratio (SSR) by 104.88%, 82.12%, and 119.73%, respectively. This work is performed using a powerful tool 3D Sentaurus TCAD using a well-calibrated structure. All the results pave the way for GaN-FinFET as a viable candidate for label-free dielectric modulated biosensor applications.

Keywords: biosensor, biomolecules, FinFET, sensitivity

Procedia PDF Downloads 159
315 The Impact of Judeo-Christian Myth and Celtic Myth in Selected Plays of William Shakespeare

Authors: Smriti Mary Gupta

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This article intends to show strong facts of ‘Judeo-Christian myth’ and ‘Celtic myth’ in selected plays of William Shakespeare. Giving the vast proliferation of Shakespeare studies we examine the strong impact of Bible in his plays. Inevitably, for instance, the study of Shakespeare and the Bible overlaps the study of Shakespeare and religion, which justify the use of Judeo-Christian myth in his works. There is some evidence that Shakespeare had read and used the ‘Geneva Bible’ in his works. The glimpse of parables and references of Biblical myth can be seen very clearly in Macbeth, King Lear and Measure for Measure. Defining a religion based on myths is difficult because it is built upon a belief of large number of people in the society. The Judeo-Christian myth which is based on the Bible, Celtic religious myth will also be discussed in this paper which had a strong impact on the audience of sixteenth century and it is still continuing at the present time.

Keywords: Celtic myth, Geneva Bible, Judeo-Christian myth, Shakespearean plays

Procedia PDF Downloads 404
314 Analysis of Q-Learning on Artificial Neural Networks for Robot Control Using Live Video Feed

Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

Procedia PDF Downloads 349
313 A 4-Month Low-carb Nutrition Intervention Study Aimed to Demonstrate the Significance of Addressing Insulin Resistance in 2 Subjects with Type-2 Diabetes for Better Management

Authors: Shashikant Iyengar, Jasmeet Kaur, Anup Singh, Arun Kumar, Ira Sahay

Abstract:

Insulin resistance (IR) is a condition that occurs when cells in the body become less responsive to insulin, leading to higher levels of both insulin and glucose in the blood. This condition is linked to metabolic syndromes, including diabetes. It is crucial to address IR promptly after diagnosis to prevent long-term complications associated with high insulin and high blood glucose. This four-month case study highlights the importance of treating the underlying condition to manage diabetes effectively. Insulin is essential for regulating blood sugar levels by facilitating the uptake of glucose into cells for energy or storage. In IR individuals, cells are less efficient at taking up glucose from the blood resulting in elevated blood glucose levels. As a result of IR, beta cells produce more insulin to make up for the body's inability to use insulin effectively. This leads to high insulin levels, a condition known as hyperinsulinemia, which further impairs glucose metabolism and can contribute to various chronic diseases. In addition to regulating blood glucose, insulin has anti-catabolic effects, preventing the breakdown of molecules in the body, such as inhibiting glycogen breakdown in the liver, inhibiting gluconeogenesis, and inhibiting lipolysis. If a person is insulin-sensitive or metabolically healthy, an optimal level of insulin prevents fat cells from releasing fat and promotes the storage of glucose and fat in the body. Thus optimal insulin levels are crucial for maintaining energy balance and plays a key role in metabolic processes. During the four-month study, researchers looked at the impact of a low-carb dietary (LCD) intervention on two male individuals (A & B) who had Type-2 diabetes. Althoughvneither of these individuals were obese, they were both slightly overweight and had abdominal fat deposits. Before the trial began, important markers such as fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and Hba1c were measured. These markers are essential in defining metabolic health, their individual values and variability are integral in deciphering metabolic health. The ratio of TG to HDL is used as a surrogate marker for IR. This ratio has a high correlation with the prevalence of metabolic syndrome and with IR itself. It is a convenient measure because it can be calculated from a standard lipid profile and does not require more complex tests. In this four-month trial, an improvement in insulin sensitivity was observed through the ratio of TG/HDL, which, in turn, improves fasting blood glucose levels and HbA1c. For subject A, HbA1c dropped from 13 to 6.28, and for subject B, it dropped from 9.4 to 5.7. During the trial, neither of the subjects were taking any diabetic medications. The significant improvements in their health markers, such as better glucose control, along with an increase in energy levels, demonstrate that incorporating LCD interventions can effectively manage diabetes.

Keywords: metabolic disorder, insulin resistance, type-2 diabetes, low-carb nutrition

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312 Lipopolysaccharide Induced Avian Innate Immune Expression in Heterophils

Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

Abstract:

Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed, with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

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311 Fuzzy Logic Based Fault Tolerant Model Predictive MLI Topology

Authors: Abhimanyu Kumar, Chirag Gupta

Abstract:

This work presents a comprehensive study on the employment of Model Predictive Control (MPC) for a three-phase voltage-source inverter to regulate the output voltage efficiently. The inverter is modeled via the Clarke Transformation, considering a scenario where the load is unknown. An LC filter model is developed, demonstrating its efficacy in Total Harmonic Distortion (THD) reduction. The system, when implemented with fault-tolerant multilevel inverter topologies, ensures reliable operation even under fault conditions, a requirement that is paramount with the increasing dependence on renewable energy sources. The research also integrates a Fuzzy Logic based fault tolerance system which identifies and manages faults, ensuring consistent inverter performance. The efficacy of the proposed methodology is substantiated through rigorous simulations and comparative results, shedding light on the voltage prediction efficiency and the robustness of the model even under fault conditions.

Keywords: total harmonic distortion, fuzzy logic, renewable energy sources, MLI

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