Judith J.E

Noorul Islam University · Department of Computer Science & Engineering

To address the challenges associated with the abundance of features in software datasets, this study proposes a novel hybrid feature selection method that combines quantum particle swarm optimization (QPSO) and principal component analysis (PCA). The objective is to identify a subset of relevant features that can effectively contribute to the accur...

Computing in the cloud is an extremely significant component of the Internet, as it is now provided to the commercial sector, the educational sector, and private consumers. Data protection is an extremely important concern in modern society. Data privacy and data security are becoming more important in the context of the computer environment for th...

Accurate software defect prediction (SDP) helps to enhance the quality of the software by identifying potential flaws early in the development process. However, existing approaches face challenges in achieving reliable predictions. To address this, a novel approach is proposed that combines a two-tier-deep learning framework. The proposed work incl...

Providing security to cloud data is one of the essential problems that have needed to be addressed in recent times due to the advancement and development of security breaches in technologies. As a result, the majority of existing research efforts aim to develop various types of cryptographic techniques for ensuring the data security of cloud system...

Accurate wind power prediction is very predominant for genuine and effective power systems with high wind power perception. Wind power prediction, as well as wind power generation resources, receives the electrical energy by converting wind into rotational energy of the blades and converting rotational energy into electrical energy by the generator...

With the proliferation of software programs, predicting defects has become a big concern. Therefore, to overcome this challenge, this research introduces a new Optimized Deep Learning model. The software defect is predicted using the new Adaptive Recurrent Neural network (ARNN), wherein the hyper-parameters (weight) function is fine-tuned using the...

Swift development in wind power and extension of wind generation necessitates significant research in numerous fields. Due to this, wind power is weather dependent; it is fluctuating and is sporadic over numerous time periods. Hence, timely wind power prediction is perceived as an extensive contribution to well-grounded wind power prediction with c...

Data mining is utilized for knowledge discovery from database for addressing issues in a particular domain. Data mining is a significant process for analyzing and obtaining required information from a large dataset. The main key objective of data mining extracts important information from the obtainable data. In general, data mining techniques incl...

Determining the similarity or distance among data objects is an important part in many research fields such as statistics, data mining, machine learning etc. There are many measures available in the literature to define the distance between two numerical data objects. It is difficult to define such a metric to measure the similarity between two cat...

Wind power has gained large importance in worldwide. An accurate wind power forecast is vital one as wind has difficult and stochastic nature. The energy output of the wind farm is depending on the weather conditions. When output predicted accurately, energy suppliers determine the production of energy sources to avoid overproduction. The predictio...

Outliers are data objects having very important and valuable information, but are rare in their datasets. Several algorithms are developed by various researchers for finding outliers from different types of datasets like multivariate datasets, time series datasets, image datasets and high dimensional datasets. These algorithms are specific to the t...

The reliability of the software can be understood using the recurrence and the development of failures or it could be recognized by framework accessibility. Software can be classified as many forms such as system software, application software, shareware, literate, freeware public domain etc. Nearly, all the frameworks used to have faults and these...

Outliers are data objects whose characteristics differ from the mainstream characteristics of the data objects in a data set. Outlier detection plays a vital role in statistics as well as in data mining. Outlier detection effects to find out hidden and important information from large data sets. It has been a research field with diverse application...

Clustering is one of the recently challenging tasks since there is an ever-growing amount of data in scientific research and commercial applications. High quality and fast document clustering algorithms are in great demand to deal with large volume of data. The computational requirements for bringing such growing amount data to a central site for c...

Efficient Overlay Based Parallel data mining architecture is introduced for improving scalability. This architecture is designed on the basis of physical networks and integration of overlay. The proposed methodology introduced an appropriate overlay network construction scheme and data allocation principle. The process of data distribution is to re...

Due to scientific progression, a variety of challenges exist in the field of information retrieval (IR). These challenges are due to the increased usage of large volumes of data. These enormous amounts of data are available from large-scale distributed networks. Centralization of these data to perform analysis is difficult. There exists a need for...

Recent advances in information technology have led to an increase in volumes of data thereby exceeding beyond petabytes. Clustering distributed document sets from a central location is difficult due to the massive demand of computational resources. So there is a need for distributed document clustering algorithms to cluster documents using distribu...

Distributed data mining paradigm is an active research area due to the enormous volume of data that are to be processed from across a wide cluster of data nodes. Document clustering algorithms are widely applied in a variety of distributed environments like peer-to-peer networks, wireless sensor networks, etc. This paper entails a comprehensive rev...

In modern environment the data management is very difficult. Large set of data is crucial to capture, store, search, analyze and visualize. Most of the application areas are in need of scalable approaches for clustering. A new technique based on particle swarm optimization and fuzzy clustering algorithm is proposed. This distributed clustering algo...

Distributed text document clustering is an emerging area that is used to improve quality in information retrieval and document organization in digital libraries. Enormous amount of data are available in large scale networks. So it is difficult to cluster data from a centralized location. A wide variety of distributed text document clustering algori...

Many of the distributed environments like internets, intranets, local area networks and wireless networks have different distributed data sources. Inorder to analyze and monitor these distributed data sources specialized data mining technologies for distributed applications are required. A variety of distributed document clustering algorithms exist...

Document clustering is one of the emerging techniques for improving quality in information retrieval and is used in digital library management system. These techniques can be applied to both centralized and distributed environment. The performance of current centralized clustering technique is reduced when applied to distributed environments such a...

A secured Hierarchically Distributed Peer-to-Peer (HDP2PC) architecture and Clustering algorithm is used to overcome the scalability problem in structured peer to peer networks. It is possible to incorporate any number of layers of nodes. The architecture is based on a multilayer overlay network of peer neighbourhoods. Supernodes, which act as repr...