A Performance Analysis of Electric Vehicles

The revolution in the automobile industry is made by electric vehicles, hybrid electric vehicles, etc. In the next few years, these technologies will replace conventional vehicle systems completely. As technology evolves very rapidly, research and development in this area are very much required. This paper presents a detailed review of a variety of electric vehicles. The technological performance review discussed here will help researchers to move the research rapidly. In this paper, the author outlines and formulates a structural framework for understanding the optimality in the case of electric vehicles and hybrid electric vehicles

ASSESSING THE COMPETITIVENESS OF FIRMS IN THE INDIAN MANUFACTURING SECTOR: AN INTER INDUSTRY ANALYSIS

This study measures the competitiveness of Indian manufacturing industries by covering 650 firms from 11 industries using the composite index approach. Firms are classified into two broad groups based on labor-capital intensity and ownership. The study found that capital-intensive industries are more competitive than labor-intensive industries. With regards to ownership of firms, the study finds that foreign-owned firms are more competitive than domestic firms. The study also divides the sample into two sub-periods based on India’s Competition Act 2002. The results reveal that competitiveness has slightly increased after the implementation of the Act

Do COVID-19 cases follow a similar transition path? Evidence from Indian states

This paper assesses the convergence of COVID-19 cases by obtaining transition paths of Indian states covering the period from August 01 to October 31, 2020. The results based on Phillips-Sul test show evidence of different transition paths. These findings are useful from the policy perspective, particularly to see whether existing efforts made for stopping the spread of COVID-19 by states/central governments are effective. • Convergence of COVID-19 cases across Indian states is investigated. • The Phillips and Sul test is applied. • Findings are in favour of different transition paths

Efficiency, productivity dynamics and determinants of productivity growth in Indian telecommunication industries: An empirical analysis

This paper examines the efficiency and productivity dynamics of the Indian telecommunication sector with the help of non-parametric Data Envelopment Analysis approach for the period 2008–2015. The study finds that the year-wise mean Total factor productivity (TFP) growth is positive in 2011 and 2013 only, where the overall TFP growth is negative. From the components of TFP growth, we find that the negative growth of the firm is due to the negative technology change, not due to the change of inefficiency of the firms. However, the mean efficiency score is positive and is backed by a scale efficiency change. Further, from the dynamic-GMM model, the study ascertains that the determinants of TFP growth are positively affected by profit intensity, advertisement intensity, import intensity and capital intensity and negatively affected by the firm's debt ratio in case of Indian telecommunication forms. This finding suggests to the policymaker that by increasing the key determinants, the performance of telecommunication firms can be increased. © 2020 John Wiley & Sons Lt

CONVERGENCE PATTERNS IN CRYPTOCURRENCY MARKETS: EVIDENCE FROM CLUB CONVERGENCE

This paper empirically examines the convergence of cryptocurrency markets with particular attention to top 30 cryptocurrencies. The study applies the novel Phillips and Sul panel convergence technique to daily closing price data of 30 cryptocurrencies for the period October 4, 2017 to May 31, 2020. The empirical findings suggest the evidence of divergence and the existence of club convergence across the cryptocurrency markets. The study finds the existence of five clubs in the top 30 cryptocurrency markets. The outcome of the study helps the investors and crypto lovers to diversify their portfolio by seeing the common transition path of the group of currencies. © 2020 World Scientific Publishing Company

Bitcoin as digital money: Its growth and future sustainability

This paper examines the comprehensive idea about the growth and future sustainability of bitcoin as a cryptocurrency. The transaction volume of bitcoin is used as the growth of the bitcoin and the bitcoin log return is used for testing the volatility which is helpful for the future sustainability of bitcoin. The study period says that the growth of bitcoin’s transaction volume is an increasing trend as more day to day transaction is minting with the exchange of Bitcoin. The study also uses ARCH & GARCH methodology to know the volatility of this emerging digital currency, and the GARCH result shows that it is a highly volatile currency. As a result, most of the governments have not given their legal status for the use of bitcoin in their country. But if bitcoin will be stable in the future, then it is easily accepted through worldwide and in the long run, people will have more faith in the cryptocurrency technology and its usability

KDE-Based Simultaneous Background Model Learning and Entropy-Based Fusion of Cascaded Features for Video Object Segmentation With Shadow Removal

Object detection with shadow removal is one of the challenging issues in computer vision. Dynamic shadow resembles a moving object’s properties, so separating this shadow from the object is a challenging task. This dynamic shadow if not eliminated, distorts the shape of the object. In this paper, a novel scheme for moving object detection and shadow removal is proposed based on the background modeling in fused feature space, and these models learn to take care of the scene dynamics. Initially, in KDE space, temporal modeling of the spatial KDE (TMS-KDE) is carried out and cascaded features of Gabor and HOG are obtained. Besides, the original video frame is transformed into YCbCr color space and LBP features are extracted. The LBP and cascaded features are fused probabilistically to generate fused feature frames which are used in background modeling. The weights for the feature fusion are determined by the proposed entropy based measure. Background modeling and model learning is a pixel based approach and the pixel is classified as either background or foreground during the learning process. We have tested our proposed method on a wide range of datasets which includes ATON-CVRR, LASIESTA, CD-net, Kaggle, PETS 2006, SGM-RGBD, SBMI 2015, SBMnet 2016 and VIRAT. The proposed scheme is found to take care of different shadow conditions while detecting the moving object. The performance of the proposed scheme is found to be superior to that of many existing schemes

Productivity growth, efficiency change and source of inefficiency: evidence from the Indian automobile industry

This paper investigates the productivity growth and efficiency change of selected automobile industry in India during 2009–2015. This study uses data envelopment analysis (DEA) technique to measure the productivity growth and efficiency change. The empirical findings suggest that the segments of the automobile industry, i.e., passenger vehicles, commercial vehicles and two wheelers have positive productivity growth in the recent period. However, our study found that commercial vehicles are more efficient as compared to passenger vehicles and two wheelers firms. Further, by applying DEA multistage approach to examine the sources of inefficiency. Our results reveal that excess inputs in near about 50% firms are cause of inefficiency and these inefficient firms can become efficient by targeting the peer group with the help of reducing the input sets which are overused in the production process

A calcified epidermoid cyst within right lateral ventricle: A report of a rare case

A young patient reported to neurosurgery outdoor department with symptoms of increased intracranial pressure. Noncontrast computed tomography examination showed a single calcified mass within right lateral ventricle with mild hydrocephalus. Contrast-enhanced magnetic resonance imaging revealed nonenhancing single mass within right lateral ventricle with mild hydrocephalus. Intraventricular calcified choroid papilloma/calcified epidermoid were radiological differentials. The mass was excised, removed from the lateral ventricles and found to be calcified epidermoid on gross and microscopic examination, which is rare

Is bitcoin a near stock? Linear and non-linear causal evidence from a price–volume relationship

The purpose of this paper is to examine the price–volume relationship in the bitcoin market to validate near-stock properties of bitcoin. Design/methodology/approach: Daily data of bitcoin returns, returns volatility and trading volume (TV) are utilized for the period August 17, 2010–April 16, 2017. Linear and non-linear causality tests are employed to examine price–volume relationship in the bitcoin market. Findings: The linear causality analysis indicates that the bitcoin TV cannot be used to predict return; however, the reverse causality is significant. In contrast, the non-linear causality analysis shows that there are non-linear feedbacks between the bitcoin TV and returns. The bitcoin TV, which represents new information, leads to price changes, and large positive price changes lead to increased trading activity. Similarly, in recent periods (post-break period), the results of the non-linear causality test show a unidirectional causality from TV to the volatility of returns. Research limitations/implications: This study uses the average index value of major bitcoin exchanges. But further research on this relationship using data from different bitcoin exchanges may provide further insights into the price–volume relationship of bitcoin and its near-stock properties. Practical implications: These findings from the non-linear causality analysis, therefore, suggest that investors cannot simply base their decisions on the linear dynamics of the bitcoin market. This is because new information in terms of the TV is neither linearly related to the price nor it is a one-to-one kind of relationship as most investors commonly understand it to be. Rather, investors’ decisions should be based on non-linear models, in general, and the best-fitting non-linear model, in particular. Originality/value: The study examines bitcoin’s near-stock properties in a price–volume relationship framework with the help of both linear and non-linear causality tests, which to the best of the authors’ knowledge remains unexplored