Narula Institute of Technology

About: Narula Institute of Technology is a based out in . It is known for research contribution in the topics: Quantum dot cellular automaton & Cognitive radio. The organization has 288 authors who have published 490 publications receiving 2258 citations. The organization is also known as: NiT.

New exponential operational law for measuring pollution attributes in mega-cities based on MCGDM problem with trapezoidal neutrosophic data

Abstract: In the modern era of fuzzy theory, trapezoidal neutrosophic number is an essential tool to seize the ambiguity and inaccuracy of many real-life problems. In this article, exponential operational law has been defined for trapezoidal neutrosophic numbers where the base is a positive real number and the corresponding weight is a trapezoidal neutrosophic number. The different algebraic properties of the said exponential operational law have been studied thoroughly. Two important operators namely trapezoidal neutrosophic weighted exponential arithmetic operator and trapezoidal neutrosophic weighted exponential geometric operator have been constructed by utilizing the said exponential operational law and its corresponding algebraic properties. Furthermore, the said aggregation operators are used to manifest a new multi-criteria group decision making technique which has been successfully applied to measure pollution attributes in different mega-cities. Finally, rigorous sensitivity analysis is performed to show the utility of the proposed operational law and manifested multi-criteria group decision making technique.

Trend analysis of time series rainfall data using robust statistics

Abstract: A temporal rainfall analysis was carried out for the study area, Rajahmundry city located in lower Godavari basin, India, during the period 1960–2013. Both the parametric and non-parametric approaches were envisaged for identifying the trends at different temporal scales. Linear and robust regression analysis revealed a negative trend at weekly scale during monsoon months, but failed to signify the slope at 95% confidence level. The magnitude of Sen9s slope was observed to be negative during the months of April–September. Results of the Mann–Kendall test ascertained the negative rainfall trends during the monsoon months of June and July with a significant trend at 95% confidence interval. Application of robust statistics for long term rainfall analysis helped to address the outlier9s problem in the dataset. The Mann–Kendall test rejected the null hypothesis for all months except February–May and August after exclusion of outliers. Overall, a negative trend during monsoon season and a positive trend during post-monsoon season were observed using a robust non-parametric approach. Further, good correlation was found between the total rainfall and rainy days during the study period. On average, 21.25% days of a year is considered as rainy, while heavy and extreme rainfall in this region together occupies nearly 15% of the rainy days.

QCA Gray Code Converter Circuits Using LTEx Methodology

Abstract: The Quantum-dot Cellular Automata (QCA) is the prominent paradigm of nanotechnology considered to continue the computation at deep sub-micron regime. The QCA realizations of several multilevel circuit of arithmetic logic unit have been introduced in the recent years. However, as high fan-in Binary to Gray (B2G) and Gray to Binary (G2B) Converters exist in the processor based architecture, no attention has been paid towards the QCA instantiation of the Gray Code Converters which are anticipated to be used in 8-bit, 16-bit, 32-bit or even more bit addressable machines of Gray Code Addressing schemes. In this work the two-input Layered T module is presented to exploit the operation of an Exclusive-OR Gate (namely LTEx module) as an elemental block. The “defect-tolerant analysis” of the two-input LTEx module has been analyzed to establish the scalability and reproducibility of the LTEx module in the complex circuits. The novel formulations exploiting the operability of the LTEx module have been proposed to instantiate area-delay efficient B2G and G2B Converters which can be exclusively used in Gray Code Addressing schemes. Moreover this work formulates the QCA design metrics such as O-Cost, Effective area, Delay and Cost α for the n-bit converter layouts.

A novel approach for extraction and analysis of variability of baseline

Abstract: Cardiotocography or CTG, is a technical means of continuously recording (-graphy) the fetal heart beat (-cardio) and the uterine contraction (-toco) of the mother. CTG is non-invasive, low price tool for checking the fetal status. Its introduction to the clinical routine limited the occurrence of fetal damage such as cerebral palsy as well as fetal mortality. One of the major features of fetal heart rate (FHR) is its baseline. Visual analysis by expert clinicians is used to evaluate the FHR baseline. This results in large inter and intra-observer variability in its interpretation. There are continuous efforts to develop methods to more accurately predict the baseline of FHR. There exist a relationship between FHR and the uterine contraction. In this paper we have explored effect of uterine contraction on the heart rate of the fetus and hence on the value of the baseline. Baseline is calculated by removing the acceleration, deceleration, and the portion of FHR which corresponds to uterine contraction. Depending on this value of baseline variability is calculated and classified. Our results were compared with the opinions of an obstetrician and another researcher in this field.

Sentiment Analysis Based Potential Customer Base Identification in Social Media

Abstract: This research work addresses a problem of social media domain where identification of potential customer base for advertisement is the objective of this work. Social media contains huge number of audience but every audience may not be a potential customer. This situation leads the advertisers to a wrong notion of having positive customers. This research work proposes an approach which can identify potential customers through sentiment analysis of audience’s activities. The proposed framework has four steps. In first step, clustering will be done according to type of product or service. In second step, every unique product will be identified among product type cluster. In third step, user’s sentiments will be identified related to each product or service. In fourth step, a sentiment based hierarchical clustering will be obtained based on identified sentiments. Based on these, a framework will be created to automate entire advertisement system that identifies potential customer base.