Ganesh Regulwar - Academia.edu (original) (raw)

Papers by Ganesh Regulwar

International journal of scientific research in science, engineering and technology, May 18, 2024

AIP conference proceedings, 2024

Advances in business information systems and analytics book series, Dec 28, 2023

Zenodo (CERN European Organization for Nuclear Research), Aug 18, 2020

Now for a few days, digitalization has become more common due to the quick, simple and convenient... more Now for a few days, digitalization has become more common due to the quick, simple and convenient use of ecommerce. People opt for e-shopping and online payment; ease of transportation, etc. As a result, fraud by credit card is on the rise every day. The identification of these frauds and the solution to prevent these frauds is very important. The proposed 'deep learning credit card fraud detection method' is based on various machine learning algorithms. Credit cards have now become very popular every day. As MasterCard is the most common online way to pay for any transaction online, frauds relating to the area unit are that, which means that a number of options are available for unauthorized users / hackers to take advantage of our account. Therefore, the information in your account may lose and customers may suffer from loss of money.

Lecture notes in networks and systems, 2020

The world around us is becoming increasingly complex every day and changes dynamically. The probl... more The world around us is becoming increasingly complex every day and changes dynamically. The problems that we face require adaptive and scalable systems that can offer solutions with ever-rising level of autonomy. Traditional approaches are becoming obsolete because they were designed for a simpler world. Therefore, any advancement in understanding and solving complex problems can have an impact on the entire set of disciplines in engineering, biology, sociology, etc. In this paper the ant colony optimization (ACO), genetic algorithm is evaluated and compares their performance with the novel proposed adaptive honey bee protocol (AHBeeP). The algorithms, stimulated by the supportive behavior of nature in colonies of animals and social insects, were initially applied to solve the traditional optimization problems. In today’s scenario, the main challenge is to transfer the packets of data from source system to destination system. In the proposed approach, the optimization is used for transferring the data packets based on the honey bees intelligence to communicate each other in the form of dancing language that can be useful for finding the shortest route in the wireless networks and also in optimized way of pathfinding.

2023 International Conference for Advancement in Technology (ICONAT)

International Journal of Computer Sciences and Engineering, 2019

International Journal of Advanced Research in Computer Science, 2010

V Model Represents one-to-one relationship between the documents on the left hand side and the te... more V Model Represents one-to-one relationship between the documents on the left hand side and the test activities on the right. This is not always correct. System testing not only depends on Function requirements but also depends on technical design, architecture also. Couple of testing activities is not explained in V model. This is a major exception and the V-Model does not support the broader view of testing as a continuously major activity throughout the Software development lifecycle. Paul Herzlich introduced the W-Model approach in 1993. The W-Model attempts to address shortcomings in the V-Model. Rather than focus on specific dynamic test stages, as the V-Model does, the W-Model focuses on the development products themselves. In its most generic form, the W-Model presents a standard development lifecycle with every development stage mirrored by a test activity. On the left hand side, typically, the deliverables of a development activity (for example, write requirements) is accompanied by a test activity test the requirements and so on. If your organization has a different set of development stages, then the W-Model is easily adjusted to your situation. The important thing is this: the W-Model of testing focuses specifically on the product risks of concern at the point where testing can be most effective. The main contribution in this paper is Sawtooth model and Sharktooth model. Sawtooth model is another variation of the V model. The Sawtooth model is actually an extension of the V-model. The only difference between the Sawtooth and the V-model is that prototypes are created and shown to the client for validation. Sharktooth model is more detailed view of the sawtooth model. In contrast to the sawtooth model the sharktooth model puts the manager into account. By presenting the manager a certain abstraction it also introduces new activities.

International Journal of Advanced Research in Science, Communication and Technology

This project describes "VoiEmo- A Speech Emotion Recognizer", a system for recognizing ... more This project describes "VoiEmo- A Speech Emotion Recognizer", a system for recognizing the emotional state of an individual from his/her speech. For example, one's speech becomes loud and fast, with a higher and wider range in pitch, when in a state of fear, anger, or joy whereas human voice is generally slow and low pitched in sadness and tiredness. We have particularly developed a classification model speech emotion detection based on Convolutional neural networks (CNNs), Support Vector Machine (SVM), Multilayer Perceptron (MLP) Classification which make predictions considering the acoustic features of speech signal such as Mel Frequency Cepstral Coefficient (MFCC). Our models have been trained to recognize seven common emotions (neutral, calm, happy, sad, angry, fearful, disgust, surprise). For training and testing the model, we have used relevant data from the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) dataset and the Toronto Emotional Spe...

There is a constant need for practical, efficient, and cost effective software evaluation techniq... more There is a constant need for practical, efficient, and cost effective software evaluation techniques. As the application code becomes older & older, maintaining it becomes a challenge for the enterprises due to increased cost of any further change in it. Refactoring is a technique to keep the code cleaner, simpler, extendable, reusable and maintainable. Code Clean Up Refactoring includes code refactoring to achieve removal of unused code and classes, renaming of classes methods and variables which are misleading or confusing. Code Standard Refactoring includes code refactoring to achieve the quality code. Developers should regularly refactor the code as per the Standard code lines. Refactoring leads to constant improvement in software quality while providing reusable, modular and service oriented components. It is a disciplined and controlled technique for improving the software code by changing the internal structure of code without affecting the functionalities. Code is not easily...

This paper discusses refactoring, which is one of the techniques to keep software maintainable. H... more This paper discusses refactoring, which is one of the techniques to keep software maintainable. However, refactoring itself will not bring the full benefits, if we do not understand when refactoring needs to be applied. To make it easier for a software developer to decide whether certain software needs refactoring or not, Fowler & Beck (Fowler & Beck 2000) give a list of bad code smells. Bad smells are signs of potential problems in code. Detecting and resolving bad smells, however, remain time-consuming for software engineers despite proposals on bad smell detection and refactoring tools. Numerous bad smells have been recognized, yet the sequences in which the detection and resolution of different kinds of bad smells are performed are rarely discussed because software engineers do not know how to optimize sequences or determine the benefits of an optimal sequence. To this end, we propose a detection and resolution sequence for different kinds of bad smells to simplify their detecti...

Texture describes the content of many real world images: for example, clouds, trees, bricks, hair... more Texture describes the content of many real world images: for example, clouds, trees, bricks, hair, fabric etc. all of which have textural characteristics.Feature extraction is one of the most important tasks for efficient and accurate image retrieval purpose. In this book we are going to use Cosine-modulated wavelet transform based technique for extraction of texture features. The major advantages of Cosine-modulated wavelet transform are less implementation complexity, good filter quality, and ease in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosine-modulated wavelet based features will be found to be superior to other existing methods.

Journal of emerging technologies and innovative research, 2020

Abstract: Now for a few days, digitalization has become more common due to the quick, simple and ... more Abstract: Now for a few days, digitalization has become more common due to the quick, simple and convenient use of ecommerce. People opt for e-shopping and online payment; ease of transportation, etc. As a result, fraud by credit card is on the rise every day. The identification of these frauds and the solution to prevent these frauds is very important. The proposed 'deep learning credit card fraud detection method' is based on various machine learning algorithms. Credit cards have now become very popular every day. As MasterCard is the most common online way to pay for any transaction online, frauds relating to the area unit are that, which means that a number of options are available for unauthorized users / hackers to take advantage of our account. Therefore, the information in your account may lose and customers may suffer from loss of money.

The cloud database as a service is a novel paradigm that can support several Internet-based appli... more The cloud database as a service is a novel paradigm that can support several Internet-based applications, but its adoption requires the solution of information confidentiality problems. We propose a novel architecture for adaptive encryption of public cloud databases that offers an interesting alternative to the tradeoff between the required data confidentiality level and the flexibility of the cloud database structures at design time. We demonstrate the feasibility and performance of the proposed solution through a software prototype. Moreover, we propose an original cost model that is oriented to the evaluation of cloud database services in plain and encrypted instances and that takes into account the variability of cloud prices and tenant workloads during a medium-term period.

Now each day the usage of credit cards has dramatically inflated. As grasp card will become the w... more Now each day the usage of credit cards has dramatically inflated. As grasp card will become the wellappreciated mode of payment for every on-line still as normal purchase. Cases of fraud related to these places are rising that there are several opportunities for used of our account by unauthorized individual / Hackers consequently the know-how on your account may want to loss and customer should suffer via loss of cash, for these purpose grasp card fraud Detection System detects unauthorized character through applying protection at customer registration level by means of imposing gadget unauthorized character will get entry to the account information or if it’s try to access then account are going to be block. KeywordsFraud detection, Machine Learning, Support Vector Machine, Decision Tree, Random Forest, naïve bias.