Papers by Dr. Yojna Arora
International journal of innovative research in computer science & technology, May 1, 2022
A Technique that check for dependency for one Data item to another is Association Rule which is a... more A Technique that check for dependency for one Data item to another is Association Rule which is an old Data mining approach. Which is used to identify the next product that might interest a customer. The Apriori Algorithm is applied in this for mining frequent products sets and relevant Association rule. With this algorithm we can use this for up-sell and also in cross-sell to show the Association rule with the help of the algorithm. These methods are widely used in global companies, so for the good understanding the companies used the methods to remain up to date that what customers demands with which products. The results helps the big retailers to identify a trend for customers buying patterns, which is very helpful information for the retailers to plan their big business operations.
International Journal of Advance Research and Innovative Ideas in Education, 2017
International Journal of Advance Research and Innovative Ideas in Education, 2019
An ecological Hotel is one which is fully integrated into the environment without damaging the en... more An ecological Hotel is one which is fully integrated into the environment without damaging the environment. The motive of these environment friendly properties is to save water, save energy and reduce solid waste while saving money to help protect the earth. However, they follow a strict green guidelines to ensure that the guests are staying in a safe, nontoxic, and energy efficient accommodation. The purpose of this study is to determine if green hotels actually benefitted from undertaking environmental practices and introducing these practices in marketing strategies. The paper includes an introduction about Green Hotels, its characteristics, architecture and also discusses about various issues to deal with while adopting the approach.
ACM Sigsoft Software Engineering Notes, Feb 11, 2014
Educational data mining is a new discipline, which aims at extracting useful information and thus... more Educational data mining is a new discipline, which aims at extracting useful information and thus knowledge from huge data sets present at Educational Institutions. The main aim for such a discipline is to improve the quality of education by analyzing every parameter that is related to it. This is a Non-Linear Problem. Machine Learning provides various algorithms and approaches to deal with problems related to determining education quality. For the present study, a prediction model based on the Radial Basis Function (RBF) is proposed and its aim is to predict marks obtained by students in a subject that is related to subjects taken during previous semesters. Based on the results of predicted performance thus obtained, students are categorized into groups and the students likely to fail are warned beforehand for improvement.
International journal of innovative research in engineering and management, Jun 20, 2022
Computer Science and Software Engineering, Nov 30, 2018
Deep Learning has emerged as a new area in machine learning and is applied to a number of signal ... more Deep Learning has emerged as a new area in machine learning and is applied to a number of signal and image applications. The main purpose of the work presented in this paper, is to apply the concept of a Deep Learning algorithm namely, Convolutional neural networks (CNN) in image classification. The performance of the algorithm is evaluated based on the quality metric known as Mean Squared Error (MSE) and classification accuracy. The graphical representation of the experimental results is given on the basis of MSE against the number of training epochs. The experimental result analysis based on the quality metrics and the graphical representation proves that the algorithm (CNN) gives fairly good classification accuracy for all the tested datasets.
Computer Science and Software Engineering, Aug 3, 2018
The Internet is migrating from IPv4 to IPv6. To determine the features for research test bed prod... more The Internet is migrating from IPv4 to IPv6. To determine the features for research test bed product selection, we compare the up-to-date information of IPv4 and IPv6. Currently IPv6 network penetration is still low but it is expected to grow, while IPv4 address pool is projected by Regional Internet Registry to be exhausted by the end of 2011. The reason why uptake of IPv6 is still low is because of high cost of service migration from IPv4 to IPv6, successfully used of IPv4 Network Address Translation for Intranet and unproven return of investment in IPv6 technology. This paper aims to review few migration path from IPv4 to IPV6 and some of the IPV6 products.
International journal of innovative research in computer science & technology, May 1, 2022
The reality of worldwide population growth and climate change demand that agriculture production ... more The reality of worldwide population growth and climate change demand that agriculture production can be increased. Traditional study findings which are difficult to extend to all conceivable fields since these are dependent on certain soil types, climatic circumstances, and background management combinations that aren't appropriate or transferable to all farms. There is no way for evaluating the efficacy of endless cropping system interactions (including many management practises) to crop production across the World. We demonstrate that dynamic interactions, that cannot be examined in repetitive trials, which are linked with considerable crop output variability and therefore the possibility for big yield gains, using massive databases and artificial intelligence. Our method can help to speed up agricultural research, discover sustainable methods, and meet future food demands. This is a paper attempted that at crop yield prediction using machine learning techniques with historic crop production data. For this, data has been collected from data.gov.in and data.world.
International journal of innovative research in computer science & technology, May 1, 2022
With the increasing need for more better way to consume a service during the Covid-19 pandemic, a... more With the increasing need for more better way to consume a service during the Covid-19 pandemic, as well as the need of more flexible way to register for the beds in the hospitals, this paper introduces a Web Application which is shaped to provide easy access to book a bed in the hospital for the needy. This framework connects the consumer to an online interface to register themselves and book a bed on their name and hospitals to register themselves and provide their details providing a time efficient way to ease the efforts. It securely maintains the data of users in a database working behind.
Computer Science and Software Engineering, Nov 30, 2018
Analysis of data is important to find the meaningful information contained in it. There are many ... more Analysis of data is important to find the meaningful information contained in it. There are many data storage and manipulation tools. Initially data was stored and analysed using files, tables, databases, data warehouse. However, in the current scenario of Big Data, these traditional methods are not efficient enough to do the analysis. Hadoop, open source software which provides support for distributed processing is implemented. In this paper, a detailed explanation about Hadoop and its components is given. Also, comparison of Hadoop components Pig, Hive and Map Reduce with traditional methods is explained.
International journal of computer applications, May 16, 2014
Forecasting is a method of making statements about certain event whose actual results have not be... more Forecasting is a method of making statements about certain event whose actual results have not been observed. It seems to be an easy process but is actually not. It requires a lot of analysis on current and past outcomes in order to give timely and accurate timely forecasted results.Radial Basis Function (RBF) is a method proposed in machine learning for making predictions and forecasting. It has been used in various real time applications such as weather forecasting, load forecasting, forecasting about number of tourist and many such applications. The paper includes a detailed survey on RBF network on the basis of its evolution and applications. It also covers explanation about combination of RBF with other techniques such as Fuzzy, Neural Networkand Genetic Algorithm.
Advances in intelligent systems and computing, Sep 30, 2022
Data processing and analysis has become difficult due the increase in data availability. Traditio... more Data processing and analysis has become difficult due the increase in data availability. Traditional methods are inefficient in handling it. So, the need is to analyze and process data in a parallel way. Haddoop solved the problem to some extent but it is difficult to be deployed and require upgraded hardware requirements. This paper proposed a framework for providing support of Hadoop as Service. An algorithm is implemented for data identification and lastl the proposed framework is compared with current system on certain parameters.
International journal of computer applications, Mar 15, 2017
In modern world, we are highly dependent upon computer for most of our works. As we know, all com... more In modern world, we are highly dependent upon computer for most of our works. As we know, all computers are controlled by software. So, to operate a computer in a proper manner, software reliability is very necessary. Software Reliability is the probability of failure-free software operation for a specified period of time in a specified environment. The high complexity of software is the major contributing factor of Software Reliability problems. Various approaches can be used to improve the reliability of software, however, it is hard to balance development time and budget with software reliability. For good reliability, two approaches have to be used, namely, reactive and proactive approach. This paper provides an overview of Software reliability, hardware reliability, reactive and proactive approaches.
Advances in intelligent systems and computing, Nov 20, 2018
Big Data is too large to be handled by traditional methods for analysis. It is a new ubiquitous t... more Big Data is too large to be handled by traditional methods for analysis. It is a new ubiquitous term, which describes huge amount of data. Dealing with “Variety”, one of the five characteristics of Big Data is a great challenge. Variety means a range of formats such as structured tables, semi-structured log files, and unstructured text, audio, and video data. Every format of data has its unique framework for analyzing it. In this paper, we present a detailed study about various frameworks for analyzing structured, semi-structured, and unstructured data individually. In addition, some frameworks, which deal with all the three formats together, are also explained.
International journal of computer applications, Dec 17, 2015
In the current scenario, big data is the biggest challenge for the industries to deal with. It is... more In the current scenario, big data is the biggest challenge for the industries to deal with. It is characterized by Huge Volume, Heterogeneous unidentified sources, High rate of data generation, inability to extract value information from irrelevant data. There are many approaches been put forward for dealing with this Big Data, some of them are RDBMS, Hadoop, Cloud Computing etc. This review article includes an elicitation of definitions of Big Data from some previous work, its characteristics, applications, various implementation techniques proposed for dealing with Big Data. It also discusses about some of the benchmarks which are proposed by companies.
Social Science Research Network, 2020
In the recent years, Data has increased exponentially and is termed as Big Data. Data Amount, Dat... more In the recent years, Data has increased exponentially and is termed as Big Data. Data Amount, Data Speed and Data Variation are three major parameters of Big Data. There are many challenges which have tuned up out of which Data Storage, Data Analysis and Data Management are the biggest ones. In order to deal with these challenges, Machine Learning, a subset of Artificial Intelligence provides various tools and techniques. This paper gives a detail about Big Data and Machine Learning. It also includes detailed literature review on various Big Data case studies which are solved by Machine Learning Techniques.
International Journal of Advance Research and Innovative Ideas in Education, 2018
Apple Academic Press eBooks, Dec 15, 2021
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Papers by Dr. Yojna Arora