Nidhi Arora

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Verified

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• Doctor of Philosophy
• Professor (Associate) at University of Delhi

Evolving densely connected communities of nodes in the real life complex networks is a computationally extensive (NP hard) problem. Nature based evolutionary heuristic algorithms provide an effective solution to such kind of problems. However, very few evolutionary approaches have been tested on this domain with most of them applying real time oper...

Community structure identification is an important area of research in complex social networks. Uncovering hidden communities in social networks data can help us to visualize and analyze various behavioral and structural phenomenon’s occurring in social networks. Detecting communities in networks implies identification of set of clusters that show...

Community identification plays an important role in classifying highly cohesive functional subunits from a larger complex networked environment. Central nodes in these communities are primary agents for regulating information flow locally within and globally across the communities. The significant contribution of this chapter is a novel metric to i...

Influence maximization is a fundamental problem in the study of complex relationship networks, such as viral marketing in business application areas. It is directed towards extracting a minimal (or k-sized) subset of most influential nodes with largest cascading effect across the network as per seeding budget. The problem is categorized as NP hard...

Non-alcoholic fatty liver disease (NAFLD) is a chronic medical ailment characterized by accumulation of excessive fat in the liver of non-alcoholic patients. In absence of any early visible indications, application of machine learning based predictive techniques for early prediction of NAFLD are quite beneficial. The objective of this paper is to p...

Background: Nature Inspired Optimization techniques are meta-heuristic techniques which are inspired from nature’s laws and behavioral patterns. This field of study comes under artificial intelligence space search techniques which involve space explorations and exploitations to search for solutions while involving randomness in overall procedure. T...

Currently, there is a notable prevalence of substantial traffic congestion and frequent vehicular accidents on roadways in contemporary times. Amalgamation of latest front-line technologies involving Internet of Things (IoT) and image classification has immense potential to advance the progress of a proficient traffic regulation system. To mitigate...

Mental health disorders are primarily life style driven disorders, which are mostly unidentifiable by clinical or direct observations, but act as a silent killer for the impacted individuals. Using machine learning (ML), the prediction of mental ailments has taken significant interest in medical informatics community especially when clinical indica...

Multiple Criteria Decision Making has been one of the powerful and structured approach in solving real world problems in the past. The aim is to determine the best alternative based on multiple criteria. It has shown a remarkable performance in the field of education. In order to gain insights into the existing body of research in this area, a bibl...

Cotton plant (Gossypium herbaceum), is one of the significant fiber crop grown worldwide. However, the crop is quite prone to leaves diseases, for which deep learning (DL) techniques can be utilized for early disease prediction and prevent stakeholders from losing the harvest. The objective of this paper is to develop a novel ensemble based deep co...

Groundnut (Arachis hypogaea L.), is the sixth-most significant leguminous oilseed crop grown all over worldwide. Groundnut, due to its high content of various dietary fibers, is classified as a valuable cash, staple and a feed crop for millions of households around the world. However, due to varied environmental factors, the crop is quite prone to...

Artificial intelligence (AI) based automated disease prediction has recently taken a significant place in the field of health informatics. However, due to unavailability of real time large scale medical data, the dynamic learning of prediction models remains principally subsided. This paper, therefore proposes a dynamic predictive modelling framewo...

Castor leaves, which come from the castor plant, are large, glossy leaves that are typically green or greenish-blue in color. The leaves are palmate, meaning that they have several pointed lobes radiating from a central point, and can measure up to 2 feet (60 cm) in diameter. Castor leaves are often used in traditional medicine, particularly in Ayu...

Proceedings of National conference on emerging trends in Information Technology held on 1-2August 2019 , Kalindi College, University of Delhi.

Study of relationships/interactions among students and teachers in structured learning environments have been a keen area of interests among educational analysts since decades. These relationships have been found to have direct as well as indirect impacts on the performance of students through varied interdisciplinary researches. The study presente...

Recent research in nature based optimization algorithms is directed towards analyzing domain specific enhancements for improving results optimality. This paper proposes an Enhanced Group Search Optimization (E-GSO) algorithm, a variant of the nature based Group Search Optimization (GSO) algorithm to detect communities in complex networks with bette...

Various evolving approaches have been extensively applied to evolve densely connected communities in complex networks. However these techniques have been primarily single objective optimization techniques, which optimize only a specific feature of the network missing on other important features. Multiobjective optimization techniques can overcome t...