arXiv subjects

Supratim Das

Publications and source records attributed to Supratim Das.

12 recordsLinked to original sources

arXiv2025

Analyzing Skill Element in Online Fantasy Cricket

Online fantasy cricket has emerged as large-scale competitive systems in which participants construct virtual teams and compete based on real-world player performances. This massive growth has been accompanied by important questions about whether outcomes are primarily driven by skill or chance. We develop a statistical framework to assess the role of skill in determining success on these platforms. We construct and analyze a range of deterministic and stochastic team selection strategies, based on recent form, historical statistics, statistical optimization, and multi-criteria decision making. Strategy performance is evaluated based on points, ranks, and payoff under two contest structures Mega and 4x or Nothing. An extensive comparison between different strategies is made to find an optimal set of strategies. To capture adaptive behavior, we further introduce a dynamic tournament model in which agent populations evolve through a softmax reweighting mechanism proportional to positive payoff realizations. We demonstrate our work by running extensive numerical experiments on the IPL 2024 dataset. The results provide quantitative evidence in favor of the skill element present in online fantasy cricket platforms.

cs.GT↗

arXiv2025

Analysing Skill Predominance in Generalized Fantasy Cricket

In fantasy sports, strategic thinking-not mere luck-often defines who wins and who falls short. As fantasy cricket grows in popularity across India, understanding whether success stems from skill or chance has become both an analytical and regulatory question. This study introduces a new limited-selection contest framework in which participants choose from four expert-designed teams and share prizes based on the highest cumulative score. By combining simulation experiments with real performance data from the 2024 Indian Premier League (IPL), we evaluate whether measurable skill emerges within this structure. Results reveal that strategic and informed team selection consistently outperforms random choice, underscoring a clear skill advantage that persists despite stochastic variability. The analysis quantifies how team composition, inter-team correlation, and participant behaviour jointly influence winning probabilities, highlighting configurations where skill becomes statistically dominant. These findings provide actionable insights for players seeking to maximise returns through strategy and for platform designers aiming to develop fair, transparent, and engaging skill-based gaming ecosystems that balance competition with regulatory compliance.

stat.AP↗

arXiv2024

Privacy-preserving federated prediction of pain intensity change based on multi-center survey data

Background: Patient-reported survey data are used to train prognostic models aimed at improving healthcare. However, such data are typically available multi-centric and, for privacy reasons, cannot easily be centralized in one data repository. Models trained locally are less accurate, robust, and generalizable. We present and apply privacy-preserving federated machine learning techniques for prognostic model building, where local survey data never leaves the legally safe harbors of the medical centers. Methods: We used centralized, local, and federated learning techniques on two healthcare datasets (GLA:D data from the five health regions of Denmark and international SHARE data of 27 countries) to predict two different health outcomes. We compared linear regression, random forest regression, and random forest classification models trained on local data with those trained on the entire data in a centralized and in a federated fashion. Results: In GLA:D data, federated linear regression (R2 0.34, RMSE 18.2) and federated random forest regression (R2 0.34, RMSE 18.3) models outperform their local counterparts (i.e., R2 0.32, RMSE 18.6, R2 0.30, RMSE 18.8) with statistical significance. We also found that centralized models (R2 0.34, RMSE 18.2, R2 0.32, RMSE 18.5, respectively) did not perform significantly better than the federated models. In SHARE, the federated model (AC 0.78, AUROC: 0.71) and centralized model (AC 0.84, AUROC: 0.66) perform significantly better than the local models (AC: 0.74, AUROC: 0.69). Conclusion: Federated learning enables the training of prognostic models from multi-center surveys without compromising privacy and with only minimal or no compromise regarding model performance.

cs.LG↗

arXiv2020

A New Approach for Texture based Script Identification At Block Level using Quad Tree Decomposition

A considerable amount of success has been achieved in developing monolingual OCR systems for Indic scripts. But in a country like India, where multi-script scenario is prevalent, identifying scripts beforehand becomes obligatory. In this paper, we present the significance of Gabor wavelets filters in extracting directional energy and entropy distributions for 11 official handwritten scripts namely, Bangla, Devanagari, Gujarati, Gurumukhi, Kannada, Malayalam, Oriya, Tamil, Telugu, Urdu and Roman. The experimentation is conducted at block level based on a quad-tree decomposition approach and evaluated using six different well-known classifiers. Finally, the best identification accuracy of 96.86% has been achieved by Multi Layer Perceptron (MLP) classifier for 3-fold cross validation at level-2 decomposition. The results serve to establish the efficacy of the present approach to the classification of handwritten Indic scripts

cs.CV↗

arXiv2019

Electrochemical kinetics of SEI growth on carbon black, I: Experiments

Growth of the solid electrolyte interphase (SEI) is a primary driver of capacity fade in lithium-ion batteries. Despite its importance to this device and intense research interest, the fundamental mechanisms underpinning SEI growth remain unclear. In Part I of this work, we present an electroanalytical method to measure the dependence of SEI growth on potential, current magnitude, and current direction during galvanostatic cycling of carbon black/Li half cells. We find that SEI growth strongly depends on all three parameters; most notably, we find SEI growth rates increase with nominal C rate and are significantly higher on lithiation than on delithiation. We observe this directional effect in both galvanostatic and potentiostatic experiments and discuss hypotheses that could explain this observation. This work identifies a strong coupling between SEI growth and charge storage (e.g., intercalation and capacitance) in carbon negative electrodes.

cond-mat.mtrl-sci↗

arXiv2019

Electrochemical kinetics of SEI growth on carbon black, II: Modeling

Mathematical models of capacity fade can reduce the time and cost of lithium-ion battery development and deployment, and growth of the solid-electrolyte interphase (SEI) is a major source of capacity fade. Experiments in Part I reveal nonlinear voltage dependence and strong charge-discharge asymmetry in SEI growth on carbon black negative electrodes, which is not captured by previous models. Here, we present a theoretical model for the electrochemical kinetics of SEI growth coupled to lithium intercalation, which accurately predicts experimental results with few adjustable parameters. The key hypothesis is that the initial SEI is a mixed ion-electron conductor, and its electronic conductivity varies approximately with the square of the local lithium concentration, consistent with hopping conduction of electrons along percolating networks. By including a lithium-ion concentration dependence for the electronic conductivity in the SEI, the bulk SEI thus modulates the overpotential and exchange current of the electrolyte reduction reaction. As a result, SEI growth is promoted during lithiation but suppressed during delithiation. This new insight establishes the fundamental electrochemistry of SEI growth kinetics. Our model improves upon existing models by introducing the effects of electrochemical SEI growth and its dependence on potential, current magnitude, and current direction in predicting capacity fade.

physics.chem-ph↗

arXiv2018

Recognition of Offline Handwritten Devanagari Numerals using Regional Weighted Run Length Features

Recognition of handwritten Roman characters and numerals has been extensively studied in the last few decades and its accuracy reached to a satisfactory state. But the same cannot be said while talking about the Devanagari script which is one of most popular script in India. This paper proposes an efficient digit recognition system for handwritten Devanagari script. The system uses a novel 196-element Mask Oriented Directional (MOD) features for the recognition purpose. The methodology is tested using five conventional classifiers on 6000 handwritten digit samples. On applying 3-fold cross-validation scheme, the proposed system yields the highest recognition accuracy of 95.02% using Support Vector Machine (SVM) classifier.

cs.CV↗

arXiv2017

A Harmony Search Based Wrapper Feature Selection Method for Holistic Bangla word Recognition

A lot of search approaches have been explored for the selection of features in pattern classification domain in order to discover significant subset of the features which produces better accuracy. In this paper, we introduced a Harmony Search (HS) algorithm based feature selection method for feature dimensionality reduction in handwritten Bangla word recognition problem. This algorithm has been implemented to reduce the feature dimensionality of a technique described in one of our previous papers by S. Bhowmik et al.[1]. In the said paper, a set of 65 elliptical features were computed for handwritten Bangla word recognition purpose and a recognition accuracy of 81.37% was achieved using Multi Layer Perceptron (MLP) classifier. In the present work, a subset containing 48 features (approximately 75% of said feature vector) has been selected by HS based wrapper feature selection method which produces an accuracy rate of 90.29%. Reasonable outcomes also validates that the introduced algorithm utilizes optimal number of features while showing higher classification accuracies when compared to two standard evolutionary algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and statistical feature dimensionality reduction technique like Principal Component Analysis (PCA). This confirms the suitability of HS algorithm to the holistic handwritten word recognition problem.

cs.CV↗

arXiv2014

New superposed elliptic solutions for a class of nonlinear evolution equations

In the context of the emergence of new classes of superposed solutions such as dn2 (x,m) \pm \sqrt m cn(x,m) dn(x,m) for a variety of nonlinear equations we present some additional new ones for the KdV and QNLS equations and show that they also admit exact solutions of the type nd2 (x,m) \pm \sqrt sd(x,m) nd(x,m). We also determine different types of superposed solutions for a generalized shallow water wave equation.

nlin.SI↗

arXiv2013

Nonlinear Dynamics of a position-dependent mass driven Duffing-type oscillator

We examine some nontrivial consequences that emerge from interpreting a position-dependent mass (PDM) driven Duffing oscillator in the presence of a quartic potential. The propagation dynamics is studied numerically and sensi- tivity to the PDM-index is noted. Remarkable transitions from a limit cycle to chaos through period doubling and from a chaotic to a regular motion through intermediate periodic and chaotic routes are demonstrated.

math-ph↗

arXiv2012

New Multi-order exact solutions for a class of nonlinear evolution equations

We seek multi-order exact solutions of a generalized shallow water wave equation along with those corresponding to a class of nonlinear systems described by the KdV, modified KdV, Boussinesq, Klein-Gordon and modified Benjamin-Bona-Mahony equation. We employ a modified version of a generalized Lame equation and subject it to a perturbative treatment identifying the solutions order by order in terms of Jacobi elliptic functions. Our multi-order exact solutions are new and hold the key feature that they are expressible in terms of an auxiliary function f in a generic way. For appropriate choices of f we recover the previous results reported in the literature.

nlin.SI↗

arXiv2010

New Exact Solutions of a Generalized Shallow Water Wave Equation

In this work an extended elliptic function method is proposed and applied to the generalized shallow water wave equation. We systematically investigate to classify new exact travelling wave solutions expressible in terms of quasi-periodic elliptic integral function and doubly-periodic Jacobian elliptic functions. The derived new solutions include rational, periodic, singular and solitary wave solutions. An interesting comparison with the canonical procedure is provided. In some cases the obtained elliptic solution has singularity at certain region in the whole space. For such solutions we have computed the effective region where the obtained solution is free from such a singularity.

nlin.SI↗