Ramesh Gadde
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Ramesh Gadde has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Aruna Kranthi Godishala
Faculty of Integrated Technologies, Universiti Brunei Darussalam, Gadong BE5101, Brunei
1 shared publication - Hayati Yassin
Universiti Brunei Darussalam
1 shared publication - Rakesh Nayak
OP Jindal University
1 shared publication
Latest Publications
- 18 October 2024
- Published by Springer Nature in SN Computer Science
- Vol. 5 (8) , 1-14
Inclusive Learning and Assessment in the Era of AI
- 18 October 2024
- Published by Springer Nature in SN Computer Science
- Vol. 5 (8) , 1-14
Inclusive Learning and Assessment in the Era of AI
- Open Access
- 12 August 2024
- Published by Elsevier in SSRN Electronic Journal
The Influence of Artificial Intelligence on Social Media Marketing
Any intelligence exhibited by a computer, robot, or other system that mimics human intellect is referred to as artificial intelligence (AI). This paper discusses the value of AI in social media marketing. The study offers a framework for understanding how social media platform marketing is impacted by artificial intelligence. The application of AI in marketing is examined in this paper, along with the advantages and disadvantages of employing AI-powered marketing tools. The essay makes the argument that AI is now a must for any marketer looking to gain a competitive edge over rivals and provides secondary data to show how businesses benefit from early AI adoption in their operations. Consequently, it recommends businesses to adopt AI technology and, specifically, that marketing directors mandate AI training for their marketing teams.
- 12 August 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessThe Influence of Artificial Intelligence on Social Media Marketing
Any intelligence exhibited by a computer, robot, or other system that mimics human intellect is referred to as artificial intelligence (AI). This paper discusses the value of AI in social media marketing. The study offers a framework for understanding how social media platform marketing is impacted by artificial intelligence. The application of AI in marketing is examined in this paper, along with the advantages and disadvantages of employing AI-powered marketing tools. The essay makes the argument that AI is now a must for any marketer looking to gain a competitive edge over rivals and provides secondary data to show how businesses benefit from early AI adoption in their operations. Consequently, it recommends businesses to adopt AI technology and, specifically, that marketing directors mandate AI training for their marketing teams.
- Open Access
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
A SURVEY ON EVOLUTION OF BIG DATA WITH HADOOP
We are living in an excessively developed technical era where internet is becoming fundamental need for all individuals. Today, our social, personal as well as professional life are revolving around world wide web. Thus, giving birth to Big Data at an incredible momentum. Traditional management tools and frameworks are proved, unfair while dealing with Big Data. This paper emphasize on number of review papers which acquainted us with the milieu of big data as well as emerging technologies helping Big Data. We also put light on the challenges increasing from the use of big data. We try to uncover correct approach to retrieve valuable information from the pile of Big Data.
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessA SURVEY ON EVOLUTION OF BIG DATA WITH HADOOP
We are living in an excessively developed technical era where internet is becoming fundamental need for all individuals. Today, our social, personal as well as professional life are revolving around world wide web. Thus, giving birth to Big Data at an incredible momentum. Traditional management tools and frameworks are proved, unfair while dealing with Big Data. This paper emphasize on number of review papers which acquainted us with the milieu of big data as well as emerging technologies helping Big Data. We also put light on the challenges increasing from the use of big data. We try to uncover correct approach to retrieve valuable information from the pile of Big Data.
- Open Access
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
An overview on architecture of botnet and techniques towards the botnet detection
As of late, botnets are the most radical of all digital attacks and turning into the major issue towards cloud computing. Botnets are the system of various traded off PCs and/or cell phones. These gadgets are contaminated with vindictive code by botmaster and controlled as gatherings. The assailants utilize these botnets for criminal exercises, for example, DDoS, click extortion, phishing, spamming, sniffing activity and spreading new malware. The main issue is how to recognize these botnets? It turns out to be all the more fascinating for the analysts identified with digital security? This focuses us to compose an audit on botnets, its architectural structure and detection techniques.
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessAn overview on architecture of botnet and techniques towards the botnet detection
As of late, botnets are the most radical of all digital attacks and turning into the major issue towards cloud computing. Botnets are the system of various traded off PCs and/or cell phones. These gadgets are contaminated with vindictive code by botmaster and controlled as gatherings. The assailants utilize these botnets for criminal exercises, for example, DDoS, click extortion, phishing, spamming, sniffing activity and spreading new malware. The main issue is how to recognize these botnets? It turns out to be all the more fascinating for the analysts identified with digital security? This focuses us to compose an audit on botnets, its architectural structure and detection techniques.
- Open Access
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Objective Quality Metric Design for Wireless Image and Video Communication
Lossless image compression is needed for applications that cannot tolerate any degradation of original imagery data, e.g., medical applications such as mammography, angiography, and x-rays. It is essential that the decompressed image does not contain any degradation in quality, since it could lead to misdiagnosis and health injury. Satellite or geographical map images are another case where distortion caused by compression cannot be tolerated.
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessObjective Quality Metric Design for Wireless Image and Video Communication
Lossless image compression is needed for applications that cannot tolerate any degradation of original imagery data, e.g., medical applications such as mammography, angiography, and x-rays. It is essential that the decompressed image does not contain any degradation in quality, since it could lead to misdiagnosis and health injury. Satellite or geographical map images are another case where distortion caused by compression cannot be tolerated.
- Open Access
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Perceptual-Based Quality Metrics For Image and Video Services
Read / Download More Articles A single, focused image can be composited by selecting the best-focused match in the stack for each image region (Clarke, 1985. Mallat, 1999). The optimal choice of parameters, including focus and aperture, for the images in a focal stack are well established (Ding, et. al., 2007). Capturing a focal stack with a large-scale high-resolution camera was implemented. Multiplex a focal stack into a single sensor image in a similar fashion as colour arrays multiplex different color channels into a RAW camera image. However, to the knowledge of the author, this camera has not yet been built. Split the aperture of a camera using circular mirrors and multiplex the result into different regions of a single photograph.
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessPerceptual-Based Quality Metrics For Image and Video Services
Read / Download More Articles A single, focused image can be composited by selecting the best-focused match in the stack for each image region (Clarke, 1985. Mallat, 1999). The optimal choice of parameters, including focus and aperture, for the images in a focal stack are well established (Ding, et. al., 2007). Capturing a focal stack with a large-scale high-resolution camera was implemented. Multiplex a focal stack into a single sensor image in a similar fashion as colour arrays multiplex different color channels into a RAW camera image. However, to the knowledge of the author, this camera has not yet been built. Split the aperture of a camera using circular mirrors and multiplex the result into different regions of a single photograph.
- Open Access
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
An Overview of Big Data Challenges, Tools and Techniques
Big Data is the large amount of data that cannot be processed by making use of traditional methods of data processing. Due to widespread usage of many computing devices such as smart phones, laptops, wearable computing devices; the data processing over the internet has exceeded more than the modern computers can handle. Due to this high growth rate, the term Big Data is envisaged. However, the fast growth rate of large data will generate numerous challenges, such as data inconsistency and incompleteness, scalability, timeliness, and security. This paper provides a brief introduction to the big data technology and its importance in the contemporary world. This paper addresses various challenges and issues that need to be emphasized to present the full influence of big data. The tools used in big data technology are also discussed in detail. This paper also discusses the characteristics of Big data and the platform used in Big Data i.e. Hadoop.
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessAn Overview of Big Data Challenges, Tools and Techniques
Big Data is the large amount of data that cannot be processed by making use of traditional methods of data processing. Due to widespread usage of many computing devices such as smart phones, laptops, wearable computing devices; the data processing over the internet has exceeded more than the modern computers can handle. Due to this high growth rate, the term Big Data is envisaged. However, the fast growth rate of large data will generate numerous challenges, such as data inconsistency and incompleteness, scalability, timeliness, and security. This paper provides a brief introduction to the big data technology and its importance in the contemporary world. This paper addresses various challenges and issues that need to be emphasized to present the full influence of big data. The tools used in big data technology are also discussed in detail. This paper also discusses the characteristics of Big data and the platform used in Big Data i.e. Hadoop.
- Open Access
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
BOTRANSACK to detect botnets using Machine learning
In the budding cyber security threats, Botnet represent the extremely critical threats being encountered by several organizations recently. Botnets are used to carry out many cybercrimes reported in the recent news. Although significantly many explorations have been undertaken on Botnet evaluation and discovery, a number of faces stayed unaddressed, for instance the competence to model detectors that deal with innovative types of Botnets. In this article, we are proposing a new Botnet detection system named BOTRANSACK using ML-centered classification skills to classify the command and control (C & C) traffic of IRC-based Botnets. Subsequently the identification process, the scheme will engender sound alarm and send text message to the admin of the system who can activate utmost suitable security activities, like hindering the corresponding IP address, placing them beneath a deeper scrutiny or acting over same apprehensive network segments.
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessBOTRANSACK to detect botnets using Machine learning
In the budding cyber security threats, Botnet represent the extremely critical threats being encountered by several organizations recently. Botnets are used to carry out many cybercrimes reported in the recent news. Although significantly many explorations have been undertaken on Botnet evaluation and discovery, a number of faces stayed unaddressed, for instance the competence to model detectors that deal with innovative types of Botnets. In this article, we are proposing a new Botnet detection system named BOTRANSACK using ML-centered classification skills to classify the command and control (C & C) traffic of IRC-based Botnets. Subsequently the identification process, the scheme will engender sound alarm and send text message to the admin of the system who can activate utmost suitable security activities, like hindering the corresponding IP address, placing them beneath a deeper scrutiny or acting over same apprehensive network segments.
- Open Access
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Light weight frame work in network security for the health care to identify botnet in IoT by using stack ensemble deep learning
Botnets are harmful cyber threats that can cause billion losses to the global economy. To detect them quickly, Network analysis approach is proposed. Our approach is Light weight method for classifying network traffic in large traffic. It uses Seven features that are quick to compute and can analyze frames in 1 to 2 seconds. Botnet attacks can carry out a variety of criminal activities besides aim of causing harm and collecting data from vulnerable machines, we used Software Defined Networks, which is capable of recognizing botnet behavior by utilizing stack ensemble machine learning approach and detection of related botnet attacks.
- 1 January 2024
- Published by Elsevier in SSRN Electronic Journal
Open AccessLight weight frame work in network security for the health care to identify botnet in IoT by using stack ensemble deep learning
Botnets are harmful cyber threats that can cause billion losses to the global economy. To detect them quickly, Network analysis approach is proposed. Our approach is Light weight method for classifying network traffic in large traffic. It uses Seven features that are quick to compute and can analyze frames in 1 to 2 seconds. Botnet attacks can carry out a variety of criminal activities besides aim of causing harm and collecting data from vulnerable machines, we used Software Defined Networks, which is capable of recognizing botnet behavior by utilizing stack ensemble machine learning approach and detection of related botnet attacks.