Saibal K. Pal

Bio: Saibal K. Pal is an academic researcher from Defence Research and Development Organisation. The author has contributed to research in topics: Encryption & Government. The author has an hindex of 14, co-authored 119 publications receiving 1122 citations. Previous affiliations of Saibal K. Pal include Analysis Group.

SEIR and Regression Model based COVID-19 outbreak predictions in India

Abstract: COVID-19 pandemic has become a major threat to the country. Till date, well tested medication or antidote is not available to cure this disease. According to WHO reports, COVID-19 is a severe acute respiratory syndrome which is transmitted through respiratory droplets and contact routes. Analysis of this disease requires major attention by the Government to take necessary steps in reducing the effect of this global pandemic. In this study, outbreak of this disease has been analysed for India till 30th March 2020 and predictions have been made for the number of cases for the next 2 weeks. SEIR model and Regression model have been used for predictions based on the data collected from John Hopkins University repository in the time period of 30th January 2020 to 30th March 2020. The performance of the models was evaluated using RMSLE and achieved 1.52 for SEIR model and 1.75 for the regression model. The RMSLE error rate between SEIR model and Regression model was found to be 2.01. Also, the value of R0 which is the spread of the disease was calculated to be 2.02. Expected cases may rise between 5000-6000 in the next two weeks of time. This study will help the Government and doctors in preparing their plans for the next two weeks. Based on the predictions for short-term interval, these models can be tuned for forecasting in long-term intervals.

Comparative Study of Firefly Algorithm and Particle Swarm Optimization for Noisy Non- Linear Optimization Problems

Abstract: There are various noisy non-linear mathematical optimization problems that can be effectively solved by Metaheuristic Algorithms. These are iterative search processes that efficiently perform the exploration and exploitation in the solution space, aiming to efficiently find near optimal solutions. Considering the solution space in a specified region, some models contain global optimum and multiple local optima. In this context, two types of meta-heuristics called Particle Swarm Optimization (PSO) and Firefly algorithms were devised to find optimal solutions of noisy non-linear continuous mathematical models. Firefly Algorithm is one of the recent evolutionary computing models which is inspired by fireflies behavior in nature. PSO is population based optimization technique inspired by social behavior of bird flocking or fish schooling. A series of computational experiments using each algorithm were conducted. The results of this experiment were analyzed and compared to the best solutions found so far on the basis of mean of execution time to converge to the optimum. The Firefly algorithm seems to perform better for higher levels of noise.

Trend Analysis and Forecasting of COVID-19 outbreak in India

Abstract: COVID-19 is spreading really fast around the world. The current study describes the situation of the outbreak of this disease in India and predicts the number of cases expected to rise in India. The study also discusses the regional analysis of Indian states and presents the preparedness level of India in combating this outbreak. The study uses exploratory data analysis to report the current situation and uses time-series forecasting methods to predict the future trends. The data has been considered from the repository of John Hopkins University and covers up the time period from 30th January 2020 when the first case occurred in India till the end of 24th March 2020 when the Prime Minister of India declared a complete lockdown in the country for 21 days starting 25th March 2020. The major findings show that number of infected cases in India is rising quickly with the average infected cases per day rising from 10 to 73 from the first case to the 300th case. The current mortality rate for India stands around 1.9. Kerala and Maharashtra are the top two infected states in India with more than 100 infected cases reported in each state, respectively. A total of 25 states have reported at least one infected case, however only 8 of them have reported deaths due to COVID-19. The ARIMA model prediction shows that the infected cases in India may reach up to 700 thousands in next 30 days in worst case scenario while most optimistic scenario may restrict the numbers up to 1000-1200. Also, the average forecast by ARIMA model in next 30 days is around 7000 patients from the current numbers of 536. Based on the forecasting model by Holts linear trends, an expected 3 million people may get infected if control measures are not taken in the near future. This study will be useful for the key stakeholders like Government Officials and Medical Practitioners in assessing the trends for India and preparing a combat plan with stringent measures. Also, this study will be helpful for data scientists, statisticians, mathematicians and analytics professionals in predicting outbreak numbers with better accuracy.

SEIR and Regression Model based COVID-19 outbreak predictions in India

Abstract: COVID-19 pandemic has become a major threat to the country. Till date, well tested medication or antidote is not available to cure this disease. According to WHO reports, COVID-19 is a severe acute respiratory syndrome which is transmitted through respiratory droplets and contact routes. Analysis of this disease requires major attention by the Government to take necessary steps in reducing the effect of this global pandemic. In this study, outbreak of this disease has been analyzed for India till 30th March 2020 and predictions have been made for the number of cases for the next 2 weeks. SEIR model and Regression model have been used for predictions based on the data collected from John Hopkins University repository in the time period of 30th January 2020 to 30th March 2020. The performance of the models was evaluated using RMSLE and achieved 1.52 for SEIR model and 1.75 for the regression model. The RMSLE error rate between SEIR model and Regression model was found to be 2.01. Also, the value of R0 which is the spread of the disease was calculated to be 2.02. Expected cases may rise between 5000-6000 in the next two weeks of time. This study will help the Government and doctors in preparing their plans for the next two weeks. Based on the predictions for short-term interval, these models can be tuned for forecasting in long-term intervals.

Digital Watermarking

Abstract: Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

A comprehensive review of firefly algorithms

Abstract: The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved using the firefly algorithm and its variants. In order to use the algorithm to solve diverse problems, the original firefly algorithm needs to be modified or hybridized. This paper carries out a comprehensive review of this living and evolving discipline of Swarm Intelligence, in order to show that the firefly algorithm could be applied to every problem arising in practice. On the other hand, it encourages new researchers and algorithm developers to use this simple and yet very efficient algorithm for problem solving. It often guarantees that the obtained results will meet the expectations.

[ACM Press the 2nd ACM Workshop - Zurich, Switzerland (2010.11.02-2010.11.02)] Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building - BuildSys \'10 - Occupancy-driven energy management for smart building automation

Abstract: Buildings are among the largest consumers of electricity in the US. A significant portion of this energy use in buildings can be attributed to HVAC systems used to maintain comfort for occupants. In most cases these building HVAC systems run on fixed schedules and do not employ any fine grained control based on detailed occupancy information. In this paper we present the design and implementation of a presence sensor platform that can be used for accurate occupancy detection at the level of individual offices. Our presence sensor is low-cost, wireless, and incrementally deployable within existing buildings. Using a pilot deployment of our system across ten offices over a two week period we identify significant opportunities for energy savings due to periods of vacancy. Our energy measurements show that our presence node has an estimated battery lifetime of over five years, while detecting occupancy accurately. Furthermore, using a building simulation framework and the occupancy information from our testbed, we show potential energy savings from 10% to 15% using our system.

Secure integration of asymmetric and symmetric encryption schemes

Abstract: This paper shows a generic and simple conversion from weak asymmetric and symmetric encryption schemes into an asymmetric encryption scheme which is secure in a very strong sense- indistinguishability against adaptive chosen-ciphertext attacks in the random oracle model. In particular, this conversion can be applied efficiently to an asymmetric encryption scheme that provides a large enough coin space and, for every message, many enough variants of the encryption, like the ElGamal encryption scheme.