Papers by Dr. GUNJAN MUKHERJEE
TayLor and Francis
The model-based approach for carrying out classification and identification of tasks has led to t... more The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines:
COSMOSYS conference proceedings, 2024
The myocardial infarction (MI) is the deadly state of heart attack bearing probable risk of death... more The myocardial infarction (MI) is the deadly state of heart attack bearing probable risk of death. The early detection of such state can easily save the human life. The ECG or electrocardiogram can be the good mean of detection of myocardial infarction of any cardiac patient. The interpretation of ECG waveform can be done by the deep learning-based Convolution Neural Network (CNN) model. In the present study, the accuracy of such work has been enhanced by appointing ensemble model consisting of the CNN with Random Forest (RF). The extraction of features from the ECG has been taken place at CNN layer followed by myocardial detection at the RF layer. The PCA has been used to estimate feature reduction followed by encoding of labeled multi-modal data. Signal of ECG data is measured through visibly fluctuation of HRV compared to the adjacent beats. The hyper-parameters have been evaluated before processing of the whole data in CNN resulting into considerable performance gain. The result obtained has got better score over the other conventional classifiers like ANN and SVM with the estimated accuracy value of 98%. Rhythm measurement has also been done through SDNN, RMSSD, and prediction of results were evaluated through the metrics of Precision, Recall, accuracy, and ROC curve in order to detect risk factors in early phase of time with the consequences of reduction in the death rate.
Advances in systems analysis, software engineering, and high performance computing book series, Apr 28, 2023
Aerial views of the scenes captured by UAV or drone have become very familiar as they easily cove... more Aerial views of the scenes captured by UAV or drone have become very familiar as they easily cover the wide view of the scene with different terrain types and landscapes. The detection of the scene images captured by drone and their subparts have been done on the basis of simple image processing approach involving the pixel intensity information. Many computer vision-based algorithms have successfully performed the tasks of segmentation. The manual approach of such segmentation has become time consuming, resource intensive, and laborious. Moreover, the perfection of segmentation on the irregular and noisy images captured by the drones have been lowered to greater extents with application of machine learning algorithms. The machine learning-based UNet model has successfully performed the task of segmentation, and the performance has been enhanced due to optimization. This chapter highlights the different variations of the model and its optimization towards the betterment of accuracy.
Indian Scientific Journal Of Research In Engineering And Management, Jan 3, 2024
Robotic systems often require engineers to write code to specify the desired behaviour of the rob... more Robotic systems often require engineers to write code to specify the desired behaviour of the robots. This process is slow, costly, and inefficient, as it involves multiple iterations and manual tuning. ChatGPT is a tool that leverages a large language model (LLM) to enable natural language interaction, code generation, and learning from feedback for robotic applications. ChatGPT allows users, who may not have technical expertise, to provide high-level instructions and feedback to the LLM, while observing the robot's performance. ChatGPT can produce code for various scenarios of robots, using the LLM's knowledge to control different robotic factors. ChatGPT can also be integrated with other platforms, such as Snapchat and Duolingo, to enhance the user experience and management. ChatGPT is a novel tool that facilitates a new paradigm in robotics, where users can communicate with and teach robots using natural language.
Time and safety are two important considerations in our daily lives. The number of kitchen-relate... more Time and safety are two important considerations in our daily lives. The number of kitchen-related accidents in both residential and commercial kitchens has increased recently. People frequently enter kitchens to prepare meals. But, if there is a gas cylinder leak, the scenario might get serious. Our goal is to use Internet of Things to lower the dangers in kitchen. IoT solutions, such as remote monitoring of the entire kitchen, can help prevent these accidents. To put this research into practice, hardware and software will both be used.Hardware-wise, Servo motor, Flame sensor, temperature, humidity, and gas sensors, Arduino UNO, load cell Node MCU, and so on have all been used. From a software standpoint, mobile apps and integrated Node MCU have been used.. Results from our system are sent as SMS. The kitchen's gas leaks can be monitored by the system, which expedites reaction times in the event of a leak. If a gas leak occurs at day or night, someone may accidentally turn on the light, which could result in anexplosive incident. The primary power supply will immediately cut off to avoid that. The associated alert alarm can provide the safeguard to the users by generating the time tined response.observing and alerting the user to kitchen appliances, such as Cylinder.
Journal of Electrical Systems, 2024
In the pursuit of optimizing renewable energy sources, the selection of solar plant installation ... more In the pursuit of optimizing renewable energy sources, the selection of solar plant installation sites presents a complex decision-making challenge that involves multiple criteria. This research introduces a groundbreaking algorithm, leveraging quantum computing techniques to enhance Multi-Criteria Decision Making (MCDM) for solar plant site selection. The proposed algorithm harnesses the superposition and entanglement properties of quantum bits to evaluate extensive datasets and criteria with unprecedented speed and accuracy. By integrating quantum versions of established MCDM methods such as the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the algorithm provides a sophisticated tool for decision-makers. The research demonstrates the algorithm's superiority over classical methods through rigorous simulation and validation processes. The findings suggest that quantum-enhanced MCDM can significantly streamline the solar plant site selection, paving the way for a more efficient deployment of solar energy infrastructure and contributing to a sustainable energy future.
Jornal of Electrical systems , 2024
In both developing and developed countries, cancer has become one of the most fearsome health ail... more In both developing and developed countries, cancer has become one of the most fearsome health ailments in the 21st century. Among the different variants of cancer, colon cancer is the 3rd most prevalent cancer globally and the 2nd deadliest form of cancer. Early diagnosis is very critical for the successful treatment of colon cancer. In recent times, machine-learning approaches have made significant strides in IoT-assisted healthcare systems. Computer-aided diagnostic systems driven by deep learning algorithms can detect colon cancer with great accuracy, assisting the medical profession in quick diagnosis and developing quick remedies against it. In our approach, we have developed a deep learning model based on convolutional neural network architecture to accurately classify and detect colon cancer. The developed model has been trained with 10,000 histopathological images of the colon, divided into two classes: colon adenocarcinoma and colon benign tissues, each containing 5000 images. We have also employed various performance metrics in our research to monitor the performance of our machine-learning model. The proposed model has been trained for 30 epochs with a batch size of 32 and achieved an overall accuracy of 98.79%.
Concurrency and Computation: Practice and Experience
Book chapter, 2024
Any person can belong to many different mental states at the different instant of time like anxie... more Any person can belong to many different mental states at the different instant of time like anxiety, joyfulness, agility, excitement, sordidness, angriness etc. The state of mental health of any person can vary over time. The mood swing is the significant phenomena which can easily make any person change his or her behavior. The trends of such mental variation cannot be tractable in manual fashion. The faulty prediction of the mental state by manual mean can provide us the wrong information about other behavioral aspects in many different human actions. ChatGPT is a generative AI model that can create natural language responses based on the user's context and personality. The feedback-based assessment and upgradation of the tool has been realized with the feeling of any human expert. We use ChatGPT as a conversational agent for mental health support. We design a framework that uses ChatGPT's skill to adapt to different user profiles and preferences and to give empathetic responses to users who need emotional help or guidance. We discuss the grave challenges and limitations of ChatGPT in this domain, such as ethical, social, and technical issues. Here about the efficiency of chatGPT has been discussed considering several related and concerned factors which can be looked upon for assessing the status of human mental health. Some suggestive approaches with the defined future directions have been conceived in this paper which definitely improve the performance issues of chatGPT application.
A potent pre-trained language model called "(Bidirectional Encoder Representations from Transform... more A potent pre-trained language model called "(Bidirectional Encoder Representations from Transformers)" is frequently utilized for a variety of natural language processing (NLP) applications, including text categorization. The basic outline of how we can use BERT for text classification which includes a pre-processing strategy that is used for tokenizing text using the BERT tokenizer to turn them into sub words. The relevant policy calls for the use of [SEP] (separator) in between sentences and the addition of special tokens at the beginning, such as [CLS] (classification). Embedding is another plan which utilise the pre-trained BERT model to obtain contextual embeddings for each token in the text Pooling which is an aggregate of the embeddings, often using pooling techniques like mean or max pooling to obtain a fixed-size representation of the input sequence. Classification layer is used to perform the classification task on top of the pooled representation for some specific task (e.g., sentiment analysis, spam detection). The model on the labelled dataset has been fine tuned. It is needed to unfreeze certain layers of BERT for better adaptation to specific tasks. The entire model thus prepared, undergo a training phase on the defined dataset with adjustment of weights of the classification layer and possibly the fine-tuned BERT layers. The model finally undergoes a validation process on the concerned data to show its performance potential. The trained model is then being employed in carrying out the prediction process on new, unseen test libraries like Hugging Face's Transformers provide easy-to-use interfaces for working with BERT and other transformer-based models. The performance of the model can be enhanced by incorporating the unique transfer learning or domain adoption process with support of substantial amounts of labelled data.
Cyber hygiene is a practice of maintaining the security and health of devices, networks, and data... more Cyber hygiene is a practice of maintaining the security and health of devices, networks, and data. It involves some guidelines to prevent cyberattacks, data breaches, and identity theft. Trust needs strong protection in the cyber system world. Cyber hygiene is essential for both individuals and organizations, as it can protect them from financial losses, reputational damage, legal consequences, physical harm, and identity theft. The term "cybersecurity" indicates vulnerabilities or other issues related to protecting personal data. Data must adhere to cyber ethics other than protection. Cyber hygiene thus gives us a notion of how trust issues in a cyber-world can be handled with better understanding of the level, volume, veracity, and the longevity of data present in cyberspace. This chapter is about finding a suitable quantitative relationship between cyber hygiene and policy of trust in micro enterprises along with different aspects of cyber hygiene problems and the possible pathways and remedies that could be taken for better functioning of these enterprises in cyber spaces.
ChatGPT is an artificial intelligence chatbot that can interact with users in a natural
and engag... more ChatGPT is an artificial intelligence chatbot that can interact with users in a natural
and engaging way. It can adapt to different conversational scenarios and provide
detailed and relevant responses. ChatGPT is based on a large language model
that has been fine-tuned using human feedback and reinforcement learning. In this
chapter, the authors explore how ChatGPT can be used for customer engagement
in various domains, such as e-commerce, education, entertainment, and health. The
benefits and challenges of using ChatGPT as a customer service agent, a personal
assistant, a tutor, a storyteller, and a health coach has been discussed. Some examples
of ChatGPT conversations with customers have been provided and its performance
and limitations has been analyzed. Finally, it can be concluded that ChatGPT is a
promising tool for enhancing customer satisfaction and loyalty, but it also requires
careful design and evaluation to ensure its safety and reliability.
Aerial views of the scenes captured by UAV or drone have become very familiar as they easily cove... more Aerial views of the scenes captured by UAV or drone have become very familiar as they easily cover the wide view of the scene with different terrain types and landscapes. The detection of the scene images captured by drone and their subparts have been done on the basis of simple image processing approach involving the pixel intensity information. Many computer vision-based algorithms have successfully performed the tasks of segmentation. The manual approach of such segmentation has become time consuming, resource intensive, and laborious. Moreover, the perfection of segmentation on the irregular and noisy images captured by the drones have been lowered to greater extents with application of machine learning algorithms. The machine learning-based UNet model has successfully performed the task of segmentation, and the performance has been enhanced due to optimization. This chapter highlights the different variations of the model and its optimization towards the betterment of accuracy.
Artificial intelligence (AI) stands out as a potent asset across diverse industries, with its pot... more Artificial intelligence (AI) stands out as a potent asset across diverse industries, with its potential within the realm of medicine proving to be exceptionally profound. This chapter takes a comprehensive journey through the myriad applications of AI in healthcare, illuminating its profound influence on patient care, disease diagnosis, therapeutic interventions, and advanced medical exploration. The fusion of AI algorithms, machine learning paradigms, and deep learning strategies empowers healthcare providers to amplify operational efficiency, precision, and the very bedrock of decision-making processes. Within this document, an intricate examination of the merits and hurdles entailed in the integration of AI into the medical domain ensues, concurrently dissecting ethical quandaries and prospective trajectories for evolution.
Linear algebra is a branch of mathematics that is widely used throughout science and engineering.... more Linear algebra is a branch of mathematics that is widely used throughout science and engineering. Linear algebra includes arithmetic operations with notation sharing. We can be able to have a better understanding of machine learning algorithms only after having a good understanding of linear algebra. Sometimes, machine learning might be pure linear algebra, involving many matrix operations; a dataset itself is often represented as a matrix. Linear algebra is used in data pre-processing, data transformations, and model evaluation. In this chapter, the basic importance of linear algebra has been discussed, and the close liaison of the subject with current research domain in machine learning and data science has been explored in the light of application of the same in solving some critical issues.
Chapter 2 Employing.ChatGPT.for.the.Management.of.Businesses.and.Decision.
International Journal of Computational Intelligence Studies
Principles and Applications of Fermentation Technology, 2018
Proceedings of International Conference on Data Science and Applications, 2021
2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), 2001
Medicinal plants are getting increasingly popular across the world for their ability to cure diff... more Medicinal plants are getting increasingly popular across the world for their ability to cure different diseases including chronic ones. The chemical compositions present in those plant leaves are main contributors for the healing characteristics. The potential of using such plants also depends on the maturity of the medicinal plant under use. The leaves with appropriate maturity can cause better healing potential. This paper presents a computer vision based approach towards identification of medicinal leaves namely Kalmegh and Tulsi against the different maturity levels. The morphological features from the processed images of leaves with different maturity levels are extracted in this work. The feature sets are subjected to Principal Component Analysis (PCA) based identification and separability measures for identification purpose. The results show that the presented morphological feature based maturity identification can be a promising method.
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Papers by Dr. GUNJAN MUKHERJEE
and engaging way. It can adapt to different conversational scenarios and provide
detailed and relevant responses. ChatGPT is based on a large language model
that has been fine-tuned using human feedback and reinforcement learning. In this
chapter, the authors explore how ChatGPT can be used for customer engagement
in various domains, such as e-commerce, education, entertainment, and health. The
benefits and challenges of using ChatGPT as a customer service agent, a personal
assistant, a tutor, a storyteller, and a health coach has been discussed. Some examples
of ChatGPT conversations with customers have been provided and its performance
and limitations has been analyzed. Finally, it can be concluded that ChatGPT is a
promising tool for enhancing customer satisfaction and loyalty, but it also requires
careful design and evaluation to ensure its safety and reliability.
and engaging way. It can adapt to different conversational scenarios and provide
detailed and relevant responses. ChatGPT is based on a large language model
that has been fine-tuned using human feedback and reinforcement learning. In this
chapter, the authors explore how ChatGPT can be used for customer engagement
in various domains, such as e-commerce, education, entertainment, and health. The
benefits and challenges of using ChatGPT as a customer service agent, a personal
assistant, a tutor, a storyteller, and a health coach has been discussed. Some examples
of ChatGPT conversations with customers have been provided and its performance
and limitations has been analyzed. Finally, it can be concluded that ChatGPT is a
promising tool for enhancing customer satisfaction and loyalty, but it also requires
careful design and evaluation to ensure its safety and reliability.