Dr Manish Madhava Tripathi - Academia.edu (original) (raw)

Papers by Dr Manish Madhava Tripathi

International Journal of Innovative Research in Computer Science and Technology

Nowadays, practically everyone, from a youngster to an adult, spends more time on online social m... more Nowadays, practically everyone, from a youngster to an adult, spends more time on online social media platforms, connecting with and exchanging information with individuals all over the world. The social network is becoming a popular means to communicate with people who live in different parts of the world. Because of the tremendous interconnectedness and information sharing enabled by the internet, social media platforms. This highlights the importance of establishing a system capable of detecting fake profiles on social media networks. There has been a lot of study done in this area utilising machine learning algorithms to identify fake profile, duplicate, spam, and bot accounts, and most of the fake profile accounts were effectively recognised using machine learning algorithms. This study discusses fake profile detection on social networks using machine learning.

In today's era, the growing ratio of Gastrointestinal (GI) diseases in human beings has become a ... more In today's era, the growing ratio of Gastrointestinal (GI) diseases in human beings has become a crucial point of notice and must be diagnosed as early as possible. There are various methods to diagnose abdomen-related problems using medical imaging techniques like ultrasound, endoscopy, Colonoscopy, abdominal CT scan and digital X-ray, etc. Endoscopy is one of the most efficient medical imaging techniques for diagnosing gastrointestinal (GI) diseases. Manual diagnosis of endoscopic images may have a possibility of committing mistakes in properly detecting gastrointestinal disorders because tiny particles are involved in endoscopic images and may be responsible for critical disorders. However, manual diagnosis may ignore such information because of less efficiency of vision and observation. To avoid such problems, various models based on soft computing and neuro-fuzzy techniques have been proposed to detect and classify various gastrointestinal disorders. In this article, the authors propose a systematic review of previous research that has been carried out using intelligent computing methods. Here, various conventional approaches are discussed and compared. This review research shows performance limitations due to complex data models, heterogeneous datasets and the absence of intelligent feature selection methods in diagnosing gastrointestinal disorders.

In current years of Covid-19 impact, COVID-19 is causing an unprecedented difficulty around the w... more In current years of Covid-19 impact, COVID-19 is causing an unprecedented difficulty around the world, affecting people's lifestyle choices. The worldwide economy, vocation, and physical and mental prosperity have all been moved by the Covid disease (COVID-19) pandemic. On behalf of students, learning losses outside of the classroom could lead to even more long-term difficulties. Or on the basis of other working areas COVID-19 impact depends on the pandemic situation in area. The AI learning is another algorithm that assumes the most awesome aspect in varying backgrounds. AI (ML) - based forecast strategies have demonstrated helpful in foreseeing perioperative results and further developing dynamic about future exercises. The reason for this paper is to cover the effect of the COVID-19 scourge on the way of life decisions of the Indian public. The application of machine learning using ANN calculation on given data set is studied in detail on what Indian society endure due to Cov...

International journal of health sciences

The breakout of Covid has occurred in recent years which had a major impact worldwide. In this sc... more The breakout of Covid has occurred in recent years which had a major impact worldwide. In this scenario, vaccination has proven to be highly successful. In a nation like India, vaccination of a big population is a difficult task. Individuals wait for hours for a vaccination slot, yet they are still unable to obtain one because information about the vaccination location and opening hours is unavailable. For this topic, we suggested a Vaccination Tracker algorithm that provides users with real-time information on vaccine openings, locations, available capacity, minimum age limit, Pin code and name of the organization, making vaccination registration a breeze. In this paper a model based of Multi-criteria Fuzzy technique is propose in which probability is generated to assign priority to the registered candidates. On the basis of the priority: Very High, High, Medium, Low, and Very low, the slot of the individual is informed regarding the availability of slots and slot is booked on the...

This paper proposes a novel confusion and diffusion algorithm for image encryption based on logis... more This paper proposes a novel confusion and diffusion algorithm for image encryption based on logistic map and cheat image. We choose the initial condition and control parameter of logistic map as the secret key. The cheat image selected from the most common images in public network, together with the chaotic matrices generated by logistic maps, is employed both in encryption and decryption processes to encrypt and recover the plain image. One cheat image can be used to encrypt a great number of plain images if the cheat image does not attract the attention of the attackers. The computer experiments such as statistical analysis, sensitivity analysis, differential attack analysis and cheat characteristic analysis, prove that the proposed image encryption algorithm is robust and secure enough to be used in practical communication. Keywords-image encryption; logistic map; cheat image;confusion;diffusion

International Journal of Research in Advent Technology, 2019

Communication plays a vital role according to the people's emotion, as emotions and gesture play ... more Communication plays a vital role according to the people's emotion, as emotions and gesture play 80% role while communication. Nowadays emotion recognition and classification are used in different areas to understand the human feelings like in the robotics, Health care, Military, Home automation, Hands-free computing, Mobile Telephony, Video game,call-center system, Marketing, etc. SER can help better interaction between the machine and the human. There are various algorithms and combination of the algorithms are available to recognize and classify the audio according to their emotion. In this paper, we attempted to investigate the episodic significant works, their technique and the impact of the approaches and the scope of the correction of the results.

Journal of Advanced Research in Applied Sciences and Engineering Technology, Mar 4, 2024

One of the world's deadliest illnesses is brain cancer. It is a cancer that often affects adults ... more One of the world's deadliest illnesses is brain cancer. It is a cancer that often affects adults as much as children. It is the least likely species to survive, and its diversity is determined by its location, sweetness and structure. The negative effects will stem from the incorrect classification of the tumour brain. Therefore, determining the specific type and rank of the tumour in its early stages is required to select a specific treatment plan. A major concern is the elimination, segmentation and detection of tumour areas infected by magnetic resonance imaging (MRI). Despite the fact that it is a laborious and tedious task done by clinical experts or radiologists whose precision depends entirely on their experience. Computer-aided technology is becoming more and more important for circumventing these limitations. This study investigates a multi-layer Deep Belief Network (DBN) technique for MRI tumour detection. The proposed model is named as Brain Tumour Deep Belief Network (BT-DBN). The BT-DBN was tested with two datasets. The results demonstrate the importance of accuracy parameters relative to the most recent approaches. The results exhibit that the BT-DBN was effective in identifying different types of tumour tissue in MR images of the brain. The precision is 99.51%, the specificity is 94.28%, and the sensitivity is 98.72%.

Abstract—Medical images plays an important role for clinical purposes and medical science. Medica... more Abstract—Medical images plays an important role for clinical purposes and medical science. Medical image can be modified easily with existing image processing tools available today. The usage of security measures such as watermarking can protect the integrity of the images. This paper will review and compare few watermarking schemes for the usage in medical imaging. The quality issues to be considered before a watermarking scheme is chosen for implementation into existing medical information system will be discussed.

Image processing techniques have played an important role in the past decades in thefield of medi... more Image processing techniques have played an important role in the past decades in thefield of medical sciences for diagnosis and treatment of patients. During diagnosis important information is embedded into RONI part of the image to itsassure integrity of the image. We propose a fragile watermarking technique to ensure the integrity of medicalimage which avoids the distortion of image in ROI by embedding the watermark informationin RONI. The watermark is comprised of patient information, hospital logo and messageattestation code computed using hash function. Earlier encryption of watermark isperformed to ensure inaccessibility of embedded data to the adversaries.

Computer Vision and Robotics, 2022

International Journal of Innovative Research in Computer Science & Technology, 2022

Fault tolerance is one of the most crucial concerns in distributed systems. Flout tolerance syste... more Fault tolerance is one of the most crucial concerns in distributed systems. Flout tolerance system is very difficult to implement due to its dynamic nature and complex services. Several research efforts consare istently being made to implement that tolerance in a distributed system. Some recent surveys try to incorporate the several fault tolerance architectures and methodologies proposed for a distributed system. This paper gives a systematic and comprehensive interpretation of different fault types, their causes, and various fault-tolerance approaches used in a distributed system. The paper presents a broad survey of various fault tolerance frameworks in the context of their basic approaches, fault applicability, and other key features. we investigate the different techniques of fault tolerance which is used in a distributed and scalable system. Scalability is an important factor in distributed Systems. It describes the ability of the system to dynamically adjust its own computing...

Studies in Big Data, 2021

Pervasive Healthcare, 2021

Journal of Informatics Electrical and Electronics Engineering (JIEEE), 2021

Online audits are the most important wellsprings of data about client feelings and are considered... more Online audits are the most important wellsprings of data about client feelings and are considered the columns on which the standing of an association is assembled. From a client's viewpoint, audit data is vital to settle on an appropriate choice with respect to an online buy. Surveys are for the most part thought to be a fair-minded assessment of a person's very own involvement in an item, however, the fundamental truth about these audits recounts an alternate story. Spammers abuse these audit stages unlawfully on account of impetuses engaged with composing counterfeit surveys, subsequently attempting to acquire a bit of leeway over contenders bringing about an unstable development of assessment spamming. This training is known as Opinion (Review) Spam, where spammers control and toxic substance surveys (i.e., making phony, untruthful, or misleading audits) for benefit or gain. It has become a typical practice for individuals to discover and to understand assessments/surveys...

Advances in Digital Crime, Forensics, and Cyber Terrorism, 2020

In this chapter, the authors explore the use of machine learning methodology for cyber forensics ... more In this chapter, the authors explore the use of machine learning methodology for cyber forensics as machine learning has proven its importance and efficiency. For classification and identification purposes in forensic science, pattern recognition algorithms can be very helpful.

International Journal of Computer Applications, 2010

Today's agent incarnations can be characterized in a number of ways ranging from simple distribut... more Today's agent incarnations can be characterized in a number of ways ranging from simple distributed objects to highly organized software with embedded intelligence. Mobile agent technology offers a new computing paradigm in which a program, in the form of a software agent, can suspend its execution on a host computer, transfer itself to another agent-enabled host on the network, and resume execution on the new host [1]. This paper is concerned with summing up a number of functionalities like node accessing, remote administration, software installation, and load balancing in a wireless network from server in real-time systems. As the sophistication of mobile software has increased over time, to have the associated threats to security, server could be able to manage and operate all the remote nodes in his network within range of the Access Point. Dynamically we can select any mobile computer and manage, operate and instruct through announcer.

In this paper we have proposed algorithms that are based on adaptive threshold method. Reversible... more In this paper we have proposed algorithms that are based on adaptive threshold method. Reversible watermarking scheme employed in this scheme improves Fourier Transform. First threshold map for image has been created and then image has been divided into different blocks. In last threshold map being set for each block. This improves image information storing capacity and original image can be obtained back. In this algorithm image can be recoded, embedded and transmitted simultaneously. The scheme can easily be used in e-diagnosis applications such as teleconsulting, tele-surgery and tele-diagnosis. 1.INTRODUCTION: Analysis of ordinary gray scale images show that binary 0s and 1s are almost equally distributed in the first several ’lower’ bit planes . However, the bias between 0s and 1s gradually increases in the ’higher’ bit-planes. In this regard transformation of the image to frequency domain is expected to be more deliverable for obtaining a large bias between 0s and 1s. For this...