arXiv subjects

Arindam Kumar Paul

Publications and source records attributed to Arindam Kumar Paul.

4 recordsLinked to original sources

arXiv2024

A mathematical model for understanding and controlling monkeypox transmission dynamics in the United States and its implications for future epidemic management

Background: Although the outbreak of human monkeypox (mpox) caused by the monkeypox virus (MPXV) has slowed down around the world, little is known about the short-term dynamics of this disease. This limited information highlights the critical need to assess the underlying interventions. Method: To identify and re-examine the key pattern of the disease, a modified logistic growth model is presented and analysed in this paper. Our main focus is on the two non-pharmaceutical interventions: policies aimed at reducing human-to-human transmission and animal-to-human transmission. We incorporated these two strategies in the model as control parameters to understand their short-term significance on the epidemic, and to analyse their strengths in minimizing the infected cases. We used mpox data set of the United States from 10 May 2022 to 31 December 2022 in the model and estimated the baseline parameters. Results: The model reveals a complying acceptance to the US data set. Model simulations highlight that preventive measures could play important roles in controlling the deadly spread of the disease in the year of 2022. During the transmission period, better outcomes could have been possible to achieve in the US if both controls were brought to action simultaneously. Conclusion: Our study reflects that continuous application of the preventive strategies might be an effective tool to prevent the short-term outbreak of mpox or similar diseases. Moreover, such strategies could play supporting roles during pre- and post-vaccination periods.

math.DS↗

arXiv2024

A Mathematical Theory for Studying and Controlling the Disinformation System Dynamics

This study explores the connection between disinformation, defined as deliberate spread of false information, and rate-induced tipping (R-tipping), a phenomenon where systems undergo sudden changes due to rapid shifts in ex-ternal forces. While traditionally, tipping points were associated with exceeding critical thresholds, R-tipping highlights the influence of the rate of change, even without crossing specific levels. The study argues that disinformation campaigns, often organized and fast-paced, can trigger R-tipping events in public opinion and societal behavior. This can happen even if the disinformation itself doesn't reach a critical mass, making it challenging to predict and control. Here, by Transforming a population dynamics model into a network model, Investigating the interplay between the source of disinformation, the exposed population, and the medium of transmission under the influence of external sources, the study aims to provide valuable insights for predicting and controlling the spread of disinformation. This mathematical approach holds promise for developing effective countermeasures against this increasingly prevalent threat to public discourse and decision-making.

math.DS↗

arXiv2024

Design & Implementation of Automatic Machine Condition Monitoring and Maintenance System in Limited Resource Situations

In the era of the fourth industrial revolution, it is essential to automate fault detection and diagnosis of machineries so that a warning system can be developed that will help to take an appropriate action before any catastrophic damage. Some machines health monitoring systems are used globally but they are expensive and need trained personnel to operate and analyse. Predictive maintenance and occupational health and safety culture are not available due to inadequate infrastructure, lack of skilled manpower, financial crisis, and others in developing countries. Starting from developing a cost-effective DAS for collecting fault data in this study, the effect of limited data and resources has been investigated while automating the process. To solve this problem, A feature engineering and data reduction method has been developed combining the concepts from wavelets, differential calculus, and signal processing. Finally, for automating the whole process, all the necessary theoretical and practical considerations to develop a predictive model have been proposed. The DAS successfully collected the required data from the machine that is 89% accurate compared to the professional manual monitoring system. SVM and NN were proposed for the prediction purpose because of their high predicting accuracy greater than 95% during training and 100% during testing the new samples. In this study, the combination of the simple algorithm with a rule-based system instead of a data-intensive system turned out to be hybridization by validating with collected data. The outcome of this research can be instantly applied to small and medium-sized industries for finding other issues and developing accordingly. As one of the foundational studies in automatic FDD, the findings and procedure of this study can lead others to extend, generalize, or add other dimensions to FDD automation.

eess.SY↗

arXiv2023

A Data-Theoretic Approach to Identifying Violent Facial Expressions in Social Crime Contexts

Human Facial Expressions plays an important role in identifying human actions or intention. Facial expressions can represent any specific action of any person and the pattern of violent behavior of any person strongly depends on the geographic region. Here we have designed an automated system by using a Convolutional Neural Network which can detect whether a person has any intention to commit any crime or not. Here we proposed a new method that can identify criminal intentions or violent behavior of any person before executing crimes more efficiently by using very little data on facial expressions before executing a crime or any violent tasks. Instead of using image features which is a time-consuming and faulty method we used an automated feature selector Convolutional Neural Network model which can capture exact facial expressions for training and then can predict that target facial expressions more accurately. Here we used only the facial data of a specific geographic region which can represent the violent and before-crime before-crime facial patterns of the people of the whole region.

cs.CV↗