Predicting the Effects of Services Trade Liberalization

Deswal Parul 한국국제경제학회 2020 International Economic Journal Vol.34 No.2

This paper uses a computable model of trade to estimate the effects of a free trade agreement on the services and the manufacturing sector. It is parameterized using 2005 data for 6 services industries and total manufacturing sector in 32 countries. The results show that a 10% reduction in both services and total manufacturing trade costs in all the countries will increase welfare by an average 10.20% across all countries. The average welfare gains across all countries are higher in case of reduction in only services trade costs compared to a 10% reduction in only manufacturing trade costs. Interestingly, however there are some countries in which trade liberalization in manufacturing brings more welfare than trade liberalization in services, while in other countries it is vice versa. The simulation results also show that implementing a trade agreement between the U.S. and the U.K. which reduces trade costs in both services and manufacturing by 10% would increase welfare in both the countries: 1.18% in the U.K. and 0.98% in the U.S. In the U.S. specialization increases in travel services, other services and manufacturing. In the U.K. specialization increases in financial services, construction services and manufacturing.

An Optimised Fuzzy Approach to Remove Mixed Noise from Images

Sweety Deswal,Surbhi Singhania,Shailender Gupta,Pranjal Garg 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.4

Mixed noises can be defined as a combination of different types of noises acting on a single carrier. There has been a mention of various mechanisms used to restore images corrupted with mixed noise in the past. This paper proposes a simple method based on fuzzy set theory and Bilateral Filter to remove mixed noises and compares it with previously mentioned techniques such as: Vector Median Filter(VMF), Vector Direction Filter (VDF), Fuzzy Peer Group Averaging (FPGA), Fuzzy Vector Median Filter (FVMF), Bilateral Filter (BF), Adaptive Bilateral Filter (ABF), Switching Bilateral Filter (SBF), Joint Bilateral Filter (JBF), and Trilateral Filter (TF) on the basis of performance metrics such as Peak Signal to Noise Ratio (PSNR), Mean Absolute Error (MAE), Mean Square Error (MSE) and Normalised Colour Difference (NCD). For the purpose of a detailed analysis, the performance of each method is evaluated by varying the image size and the noise density by implementing them in MATLAB-09. The mixed noise used in this paper is a combination of three noise i.e. poisson, impulse and Gaussian noise. The simulation and result shows that the proposed method provides better PSNR and hence better image quality than almost all the methods mentioned above.

A magneto-thermo-viscoelastic problem with fractional order strain under GN-II model

Sunita Deswal,Kapil Kumar Kalkal,Sandeep Singh Sheoran 국제구조공학회 2017 Structural Engineering and Mechanics, An Int'l Jou Vol.63 No.1

In this work, we present a theoretical framework to study the thermovisco-elastic responses of homogeneous, isotropic and perfectly conducting medium subjected to inclined load. Based on recently developed generalized thermoelasticity theory with fractional order strain, the two-dimensional governing equations are obtained in the context of generalized magneto-thermo-viscoelasticity theory without energy dissipation. The Kelvin-Voigt model of linear viscoelasticity is employed to describe the viscoelastic nature of the material. The resulting formulation of the field equations is solved analytically in the Laplace and Fourier transform domain. On the application of inclined load at the surface of half-space, the analytical expressions for the normal displacement, strain, temperature, normal stress and tangential stress are derived in the joint-transformed domain. To restore the fields in physical domain, an appropriate numerical algorithm is used for the inversion of the Laplace and Fourier transforms. Finally, we have demonstrated the effect of magnetic field, viscosity, mechanical relaxation time, fractional order parameter and time on the physical fields in graphical form for copper material. Some special cases have also been deduced from the present investigation.

CoBiD-net: a tailored deep learning ensemble model for time series forecasting of covid-19

Shastri Sourabh,Singh Kuljeet,Deswal Monu,Kumar Sachin,Mansotra Vibhakar 대한공간정보학회 2022 Spatial Information Research Vol.30 No.1

The pandemic of novel coronavirus disease 2019 (Covid-19) has left the world to a standstill by creating a calamitous situation. To mitigate this devastating effect the inception of artificial intelligence into medical health care is mandatory. This study aims to present the educational perspective of Covid-19 and forecast the number of confirmed and death cases in the USA, India, and Brazil along with the discussion of endothelial dysfunction in epithelial cells and Angiotensin-Converting Enzyme 2 receptor (ACE2) with the Covid-19. Three different deep learning based experimental setups have been framed to forecast Covid-19. Models are (i) Bi-directional Long Short Term Memory (LSTM) (ii) Convolutional LSTM (iii) Proposed ensemble of Convolutional and Bi-directional LSTM network are known as CoBiD-Net ensemble. The educational perspective of Covid-19 has been given along with an architectural discussion of multi-organ failure due to intrusion of Covid-19 with the cell receptors of the human body. Different classification metrics have been calculated using all three models. Proposed CoBiD-Net ensemble model outperforms the other two models with respect to accuracy and mean absolute percentage error (MAPE). Using CoBiD-Net ensemble, accuracy for Covid-19 cases ranges from 98.10 to 99.13% with MAPE ranges from 0.87 to 1.90. This study will help the countries to know the severity of Covid-19 concerning education in the future along with forecasting of Covid-19 cases and human body interaction with the Covid-19 to make it the self-replicating phenomena.

CoBiD-net: a tailored deep learning ensemble model for time series forecasting of covid-19

Shastri Sourabh,Singh Kuljeet,Deswal Monu,Kumar Sachin,Mansotra Vibhakar 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2

The pandemic of novel coronavirus disease 2019 (Covid-19) has left the world to a standstill by creating a calamitous situation. To mitigate this devastating effect the inception of artificial intelligence into medical health care is mandatory. This study aims to present the educational perspective of Covid-19 and forecast the number of confirmed and death cases in the USA, India, and Brazil along with the discussion of endothelial dysfunction in epithelial cells and Angiotensin-Converting Enzyme 2 receptor (ACE2) with the Covid-19. Three different deep learning based experimental setups have been framed to forecast Covid-19. Models are (i) Bi-directional Long Short Term Memory (LSTM) (ii) Convolutional LSTM (iii) Proposed ensemble of Convolutional and Bi-directional LSTM network are known as CoBiD-Net ensemble. The educational perspective of Covid-19 has been given along with an architectural discussion of multi-organ failure due to intrusion of Covid-19 with the cell receptors of the human body. Different classification metrics have been calculated using all three models. Proposed CoBiD-Net ensemble model outperforms the other two models with respect to accuracy and mean absolute percentage error (MAPE). Using CoBiD-Net ensemble, accuracy for Covid-19 cases ranges from 98.10 to 99.13% with MAPE ranges from 0.87 to 1.90. This study will help the countries to know the severity of Covid-19 concerning education in the future along with forecasting of Covid-19 cases and human body interaction with the Covid-19 to make it the self-replicating phenomena.

Genome-wide identification and functional analysis of denitrosylases (S-nitrosoglutathione reductases and NADPH-dependent thioredoxin reductases) in Brassica juncea

Babuta Priyanka,Paritosh Kumar,Deswal Renu 한국식물생명공학회 2023 Plant biotechnology reports Vol.17 No.4

S-nitrosylation is a well-known post-translational modification that modulates nitric oxide-dependent cell signaling. NADH-dependent S-nitrosoglutathione reductase (GSNOR) and NADPH-dependent thioredoxin reductase (NTR) enzymes are essential for nitric oxide/S-nitrosothiol (NO/SNO) homeostasis. GSNOR and NTR regulate denitrosylation by reducing S-nitrosoglutathione (GSNO) and thioredoxins, respectively. Genome-wide identification yielded 4 GSNOR and 12 NTR (4 each of NTRA, NTRB, and NTRC) genes in Brassica juncea. Syntenic relationship showed whole genome triplication (WGT) and tandem duplications. The phylogenetic analysis revealed clustering of BjGSNORs and BjNTRs with Arabidopsis homologs suggesting high sequence similarity within groups. Subcellular localization prediction suggested BjGSNOR localizes not only to the cytosol, but also to the Golgi apparatus and endoplasmic reticulum. BjNTRA and BjNTRB were localized in the cytoplasm and mitochondria, respectively, whereas BjNTRC localized in the chloroplast and nucleus. Several cis-acting elements involved in light responsiveness and expression analysis suggested the regulation of denitrosylation by light. The analysis of the promoter region also showed various phytohormone-regulated elements, suggesting the involvement of these enzymes in plant growth. Furthermore, GSNOR and NTR activities were higher in early growth stages. Differential spatial distributions of both the enzymes were observed with higher activity in hypocotyl in comparison with roots and cotyledons of the seedling. In flower, the highest activities were observed in carpel and least in stamens. Collectively, these findings provide an understanding of the structure, localization, and evolution of multiple copies of denitrosylases BjGSNOR and BjNTR, along with their possible roles in plant development.

Effect of heat source and gravity on a fractional order fiber reinforced thermoelastic medium

Jain, Kavita,Kalkal, Kapil Kumar,Deswal, Sunita 국제구조공학회 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.68 No.2

In this article, the theory of fractional order two temperature generalized thermoelasticity is employed to study the wave propagation in a fiber reinforced anisotropic thermoelastic half space in the presence of moving internal heat source. The whole space is assumed to be under the influence of gravity. The surface of the half-space is subjected to an inclined load. Laplace and Fourier transform techniques are employed to solve the problem. Expressions for different field variables in the physical domain are derived by the application of numerical inversion technique. Physical fields are presented graphically to study the effects of gravity and heat source. Effects of time, reinforcement, fractional parameter and inclination of load have also been reported. Results of some earlier workers have been deduced from the present analysis.

Effect of heat source and gravity on a fractional order fiber reinforced thermoelastic medium

Kavita Jain,Kapil Kumar Kalkal,Sunita Deswal 국제구조공학회 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.68 No.2

In this article, the theory of fractional order two temperature generalized thermoelasticity is employed to study the wave propagation in a fiber reinforced anisotropic thermoelastic half space in the presence of moving internal heat source. The whole space is assumed to be under the influence of gravity. The surface of the half-space is subjected to an inclined load. Laplace and Fourier transform techniques are employed to solve the problem. Expressions for different field variables in the physical domain are derived by the application of numerical inversion technique. Physical fields are presented graphically to study the effects of gravity and heat source. Effects of time, reinforcement, fractional parameter and inclination of load have also been reported. Results of some earlier workers have been deduced from the present analysis. 2010MSC: 74A15, 80A20.

POSTERS / PM-051 : ANTISENSE EXPRESSION OF EhCaBP GENE LEADS TO ENHANCED CHLOROPHYLL LEVELS AND DELAYED SENESCENCE IN TRANSGENIC TOBACCO

(G . K . Pandey),(V . S . Reddy),(R . Deswal),(A . Bhatacharya),(S . K . Sopory) 한국생화학분자생물학회 (구 한국생화학회) 1999 6th IUBMB SEOUL CONFERENCE Vol.- No.-

Propagation of plane waves in an orthotropic magneto-thermodiffusive rotating half-space

Suresh Kumar Sheokand,Rajesh Kumar,Kapil Kumar Kalkal,Sunita Deswal 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.72 No.4

The present article is aimed at studying the reflection phenomena of plane waves in a homogeneous, orthotropic, initially stressed magneto-thermoelastic rotating medium with diffusion. The enuciation is applied to generalized thermoelasticity based on Lord-Shulman theory. There exist four coupled waves, namely, quasi-longitudinal P-wave (qP), quasi-longitudinal thermal wave (qT), quasi-longitudinal mass diffusive wave (qMD) and quasi-transverse wave (qSV) in the medium. The amplitude and energy ratios for these reflected waves are derived and the numerical computations have been carried out with the help of MATLAB programming. The effects of rotation, initial stress, magnetic and diffusion parameters on the amplitude ratios are depicted graphically. The expressions of energy ratios have also been obtained in explicit form and are shown graphically as functions of angle of incidence. It has been verified that during reflection phenomena, the sum of energy ratios is equal to unity at each angle of incidence. Effect of anisotropy is also depicted on velocities of various reflected waves.