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Vehicular Traffic on road is a primary source of noise pollution. Traffic noise from the congestedVehicular Traffic on road is a primary source of noise pollution. Traffic noise from the congested busy areas of any town/city and the traffic on highways create problems for the surrounding areas, especially during the peak traffic hours, when the traffic volume is quite high accompanied by speeding vehicles. The traffic noise is produced by different types of vehicles like heavy, medium trucks/buses, various sorts of automobiles, three wheelers and two wheelers. In India, the transportation sector is proliferating and the number of vehicles operating on the roads is increasing very rapidly, leading to overcrowding on roads and huge traffic jams. The lack of awareness about various traffic rules, incautious and reckless driving and insufficient traffic- rule enforcing agencies have even deteriorated the condition. So, it has become indispensable to control and regulate the traffic noise level. The main objective of the present study is to observe and identify the pattern of vehicular traffic volume and the associated noise generated in few areas of Durgapur at different hours of the day. The noise thus generated at the designated areas has been compared with the standards prescribed by the Central Pollution Control Board. Few suggestions have been included for improvement of the ambient environmental conditions.

This paper presents a new hybrid chemical reaction optimization (HCRO) approach to find the optimal placement of Static Synchronous Compensator (STATCOM) to achieve optimal performance of power system. Optimal reactive power dispatch (ORPD) has a significant influence on optimal operation of power systems. However, getting optimal solution of ORPD is a cumbersome task for the researchers. The inclusion of flexible AC transmission system (FACTS) devices in the power system network for solving ORPD adds to its complexity. This paper presents HCRO for optimal allocation of STATCOM to minimize the transmission loss, improve voltage profile and voltage stability in a power system. It is found that the results obtained by the HCRO technique are superior to those obtained by other algorithms.

In amorphous semiconductors, the atomic order in a long range ceases to exist, but the short range order remains to some extent, giving rise thereby to a band-like structure of electron energy states similar to that of crystalline semiconductors. Amorphous semiconductors in many aspects are prioritized over crystalline semiconductors due to its low cost, easy preparation process and market demand for tailored material properties. Now a days, they have found applications in all areas where previously only crystalline semiconductors are used. In this review paper, a few recent discoveries and developments in the field of amorphous semiconductors are discussed.

The founding fathers of ancient societies and, more recently, the sovereign democratic republic envisioned a great bounty of welfare for all citizens of India and sundry in perpetuity, across all generations. Welfare measures in India have been a vexed issue for the entire interregnum, from the midnight hour when emancipation from the yoke of slavery was finally attained to the present moment, while at the same time mass prosperity and welfare has undergone multiple decennial changes and rapid if not monotone evolution in the West, inspite of the fact that mass prosperity incentivizes further industrialization and development. The pandemic has taken a diabolical toll on the national economy and in particular welfare of the masses. Herein, we conduct a data science enriched study of the standard published Pradhan Mantri Rozgar Protsahan Yojna (PMPRY as industrialization proxy) and Employee Pension Scheme data (EPS as welfare) and simulate the series based on the original series properties. We plot the level series, run unit root tests, fit the bivariate VAR (unrestricted), check for Granger causality and plot the Impulse Response Function. Conclusively, we make brief optical discernments regarding the simulated nature of the disbursements and estimated impact of the welfare scheme and conclude.

A perennial issue in the economic space is apprised debate about the nature of inflation and magnification of the Indian economy, with particular references being made to the disruptions during the pandemic. India's national income aggregates showed steady magnification in the face of economic downturns in major markets a decennium ago. But the pandemic has taken a heftily ponderous toll on the national economy. An attendant irritant is the truculent inflation trends in critical segments such as fuel. In the present study, we take up a conservative but methodical data science approach to analyze the Urban Consumer Price Index (CPI) of Fuel in India. We study the standard published time series of genuine index values. We run ADF tests with a preliminary ACF/PACF calculation and then tweak the model towards optimization with a formal ARIMA structure in RStudio. In concluding, we make rigorously informed discernments regarding the model's predictive capacity and conclude.

The pusillanimous and terpsichorean global response to the horrors of the Covid19 pandemic has been the matter of great discussion and debate. Of equal interest to the global community of predominantly academic researchers of polytomous persuasion was the effete exercise of predicting the temporal expanse and the ravagement pathways of the malfeasant infestation. The native monotone temporality of the unprecedented horrors were eventually met with and curbed by gubernatorial interventions of matchingly unprecedented magnitudes. The present paper subjects eclectic data on the said malfeasance to ensemble data science analysis, namely, analysis by ML with multiple bootstraps of Random Forests in RStudio covering heuristic causalities incident on key variables. The focal theatre of interest in the study is of course India. The composite learning is concluded harmoniously and unequivocal pronouncements made of key findings regarding the datasets.

In the present scope the pan India COVID-19 new cases in daily basis has been observed. The target is a time series data set with a span from 30.01.2020 to 04.10.2021. The study focuses on observing and anticipating different dynamical characteristics of the outbreak such as linear/non-linear, stationary/non-stationary behaviour, and probable recurrence in time frame to infer internal dynamics of the pandemic spread. Recurrence plot (RP) and Recurrence quantification analysis (RQA) has been exploited to analyse the same in phase space. The daily spread of Covid-19 in India is governed by non-stationary process with the characteristics of fractional Brownian motion. The signal is deterministic and stable having low periodicity and probable chaotic nature as found in the study.

The recent deployment of various intelligent and smart systems in Internet-of-Things (IoT) has been conceptualized from the wireless sensor network features for their actualization. The role of the deployed sensor nodes is quite significant for realizing the intended IoT applications for which sensor nodes are required to operate consistently. However, the very resource-constrained nature of sensor nodes imposes various limitations on the network performance. Out of these limitations, the one due to limited and irreplaceable energy resources is the most severe, which can down the network if not appropriately addressed. In this work, the issue mentioned above has been addressed via the formulation of energy-balanced clusters in an IoT-based heterogeneous wireless sensor network. The proposed clustering scheme takes various network parameters such as intra-cluster distances of the nodes and their respective energy status into account. This metaheuristic scheme formalizes the energy-balanced clusters independent of energy-heterogeneity deployed in the network. Moreover, the supremacy of the proposed scheme has been established int terms of network lifetime, network energy consumption, and network throughput over a state-of-the-art scheme via an extensive set of simulations and experimentation.

Gene finding techniques are based on identifying coding portions in DNA sequences. In this paper, Gene finding techniques are based on identifying coding portions in DNA sequences. In this paper, the difference between coding and non-coding sequences is studied and a criterion is developed to classify asequence into one of the two types. The species considered in Drosophila Melanogaster, and all six chromosomes are studied individually. The basic characteristic of a sequence that is considered is the distribution of the four bases A, C, G and T. A statistical test of homogeneity is used to study the difference among the types in this respect. In this connection, we also tested the GC-richness property of coding sequences, which is validated. Finally, a distance type parameter is developed for each sequence. Actually d2 , the square of the Euclidean distance of the distribution of bases from a standard distribution is considered. For the standard distribution, various choices are examined. The frequency distribution of d2 for the coding and non-coding types shows clear differences for all choices for the standard distribution. Finally a critical value of d2 is obtained to classify a sequence as coding or non-coding, which gives more than 90% accuracy for all six chromosomes.

Warm mix asphalt (WMA) is a promising green technology with the potential to replace hot mix asphalt (HMA) in road construction. The purpose of this research is to assess the efficacy of ZycoTherm WMA green technology in the construction of porous pavement. Porous pavement mixes comprised of open graded porous friction course materials with large voids reduce pressure on urban drainage systems and enhance natural water supply during rainstorms. Using WMA additive ZycoTherm and VG 30 grade bitumen, this research focused on the properties of PFC grading bituminous mixes specified by the Indian Road Congress code IRC: 129-2019. ZycoTherm is an eco-friendly nano-organic anti stripping additive that allows for lower mixing temperatures. Volumetric properties, water drain-down, permeability, and un-aged and aged abrasion resistance tests were performed on porous paving mixes with and without ZycoTherm. This study examines PFC mixtures with bitumen contents of 5.0 to 6.0 percent. The experimental results were analysed in order to determine the most vital controlling parameters. According to the results, ZycoTherm shows the potential to improve the performance properties of porous mixes.