ISI Digital Commons (Indian Statistical Institute )
Not a member yet
7571 research outputs found
Sort by
BISECTION: BlockchaIn-enabled SECure healTh Insurance prOcessiNg
No full textA health insurance policy plays a crucial financial safeguard, providing medical coverage during medical emergencies. However, the health insurance sector faces challenges like delayed claim processing, higher administrative costs, and trust issues. This paper proposes a transformative solution leveraging blockchain technology to address these issues effectively. Our solution introduces a novel blockchain-enabled health insurance processing system that streamlines critical operations and ensures fairness for all stakeholders. Various insurance procedures are encoded through smart contracts, leading to increased transparency and trust in the claim settlement process. We present a secure and privacy-preserving access control policy for sharing electronic healthcare records (EHR) with insurance companies during verification to address privacy concerns. We developed our application on Ethereum and deployed the smart contracts on the Ropsten test network, demonstrating its potential to enhance transparency, trust, and security in health insurance. Experimental results confirm our model\u27s commendable impact on health insurance processing
Cancer model and its possible control—A Z-type control approach
No full textThis paper investigates the dynamics of a three-dimensional nonlinear cancer model involving interactions among cancer cells, normal cells, and immune cells. By performing a linear stability analysis of the equilibria and investigating the Hopf bifurcation in relation to the immune cell growth rate, we reveal the possibility of chaotic behavior when radiation is absent. However, with the appropriate implementation of radiotherapy, the cancer model demonstrates stable solutions, transitioning from chaotic oscillations through period-halving bifurcation. Additionally, we propose and examine an indirect Z-control mechanism within the cancer model. Our findings indicate that using the indirect Z-controller on the immune population successfully manages chaos and adjusts the cancer cell density to a desired level. Through extensive investigation, we demonstrate the robustness of the Z-controller in managing oscillations and provide insights into determining the minimum number of immune cells needed to achieve a predetermined cancer cell density. This study underscores the importance of control mechanisms in mitigating cancer progression and highlights the potential of Z-control for therapeutic intervention strategies
Carbon pricing and household welfare: evidence from Uganda
No full textPolicymakers frequently voice concerns that carbon pricing could impair economic development in the short run, especially in low-income countries such as Uganda. Using a consumer demand system for energy and food items, we assess how households\u27 welfare, and demand for food and energy, would respond to a carbon price of USD40/tCO2. We find welfare losses of 0.2-12 per cent of household expenditure on food and fuel, due to the carbon price. Average demand for electricity and kerosene decline by 11 and 20 per cent respectively, while firewood demand rises by 10 per cent on average. We observe shifts within food consumption baskets, with declines in the demand for meat & fish, and vegetables, alongside an increase in cereal consumption. Household nutrition is adversely impacted, with declines in protein and micronutrient intake across the population. Complementary social protection policies such as cash transfers are therefore required to ease adverse effects on economic development in Uganda
CCOCSA-based multi-frame sparse coding super-resolution via mutual information-based weighted image fusion
No full textImage super-resolution (SR) is one of the most urgent requirements in many applications in computer vision. Though many techniques have been proposed to date, they are not suitable in real-life applications because of their lack of performance when the low resolution (LR) images are noisy. In the single-frame SR mechanism, the output image can not reproduce the information which is lost due to sub-sampling at the time of image formation. Multi-frame image SR technique can solve this problem to a reasonable extent. However, most of the multi-frame image SR techniques are based on image registration which is noise sensitive. The registration errors in noisy LR images deteriorate the performance of the registration process and hence the performance of the multi-frame SR algorithms. This paper addresses this problem and proposes a novel mutual information-based multi-frame sparse coding super-resolution via Chaotic Centroid-Oppositional Crow Search Optimization Algorithm (CCOCSA)-based image registration. The proposed SR algorithm is accomplished in two steps: (1) CCOCSA-based image registration and (2) Mutual information-based weighted mean multi-frame super-resolution reconstruction through sparse representation. The proposed CCOCSA is a noise-robust optimization that provides better accuracy in estimating registration parameters. We achieve this by enhancing the exploration by dynamically varying the control parameters and introducing chaos within the algorithm. The weighted mean of the registered LR frames based on mutual information provides a good noise reduction capability. Also, it gathers the information from all the LR frames on the registered weighted mean frame, which enriches the information in the reconstructed SR image. The performance of the proposed algorithm is tested through the experiments on four benchmark datasets (Vid4, McMaster, Milanfar, and Kodak) for videos and still images. We verify the performance of the proposed technique by computing four well-known quality metrics, such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Edge Keeping Index (EKI), blur-metric, and Perceptual SIMilarity (PSIM) measure. The experimental results show that the proposed SR algorithm outperforms the others quantitatively and qualitatively
Context-Committing Security of Leveled Leakage-Resilient AEAD
No full textDuring recent years, research on authenticated encryption has been thriving through two highly active and practically motivated research directions: provable leakage resilience and key-or context-commitment security. However, the intersection of both fields had been overlooked until very recently. In ToSC 1/2024, Struck and Weishäupl studied generic compositions of encryption schemes and message authentication codes for building committing leakage-resilient schemes. They showed that, in general, Encrypt-then-MAC (EtM) and MAC-then-Encrypt (MtE) are not committing while Encrypt-and-MAC (EaM) is, under plausible and weak assumptions on the components. However, real-world schemes are rarely strict blackbox constructions. Instead, while various leakage-resilient schemes follow blueprints inspired by generic compositions, they often tweak them for security or efficiency. In this paper, we study two blueprints, the first one based on EtM for one of the strongest possible levels of leakage resilience. The second one is a single-pass framework based on leveled implementations. We show that, with a careful selection of the underlying primitives such as with identical encryption and authentication keys and a collision-resistant PRF as the MAC, these blueprints are committing. Our results do not contradict the results by Struck and Weishäupl since we pose more, but practically-motivated, requirements on the components. We demonstrate the practical relevance of our results by showing that our results on those blueprints allow us to easily derive proofs that several state-of-the-art leakage-resilient schemes are indeed committing, including TEDT and its descendants TEDT2 and Romulus-T, as well as the single-pass scheme Triplex
Cooperative vs. non-cooperative R&D under uncertain probability of success
No full textThe present paper introduces incomplete information about success probability of R&D in a model of two firms interacting in R&D and production and discusses the choice between research joint venture (RJV) and non-cooperative R&D. We have shown that whenever the high-type firm prefers RJV, the low-type firm also prefers RJV, and if the low-type firm prefers non-cooperative R&D, the other firm will do the same. On the other hand, when the high-type firm prefers non-cooperative research, the low-type firm will go for RJV or non-cooperative research depending on the constellation of parameters. However, the high-type firm preferring RJV and the low-type firm preferring non-cooperative research can never occur under incomplete information, although this can be a possibility under complete information. Finally, if the R&D cost is at the intermediate level and the probability that a firm is of high type is above a critical level, RJV will occur irrespective of the type distribution of nature. RJV may also occur when both firms are low type and the corresponding probability belongs to an interval. In all other cases non-cooperative R&D will occur
Deciphering geochemical fingerprints and health implications of groundwater fluoride contamination in mica mining regions using machine learning tactics
No full textThe contribution of mica mining activities to fluoride (F−) contamination in groundwater has been chased in this study. For the purpose, groundwater samples (n = 40, replicated thrice) were collected during the post-monsoons (September–October) from a mica mining area in the Tisri block of Giridih district, Jharkhand. The study has employed a synergy of classical aquifer chemistry, statistical approaches, different indices, Self-Organising Maps (SOM), and Sobol sensitivity index (SSI) to unveil the underlying aquifer chemistry, identify the impacts of mining activities on groundwater quality and its associated health hazard. Fluoride levels varied from 0.34 to 2.8 ppm, with 40% of samples exceeding the World Health Organization\u27s permissible limit (1.5 ppm). Physicochemical analysis revealed significant differences in electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH) and major ion concentrations (Na+, HCO3−, Ca2+) between fluoride-contaminated (FC) and fluoride-uncontaminated (FU) groups. Higher Na+ and HCO3− associated with F− contaminated samples, were indicative of silicate weathering and carbonate dissolution as primary geogenic sources for this ion. Health risk assessment (HRA) revealed hazard quotient (HQ) values exceeding unity, indicating non-carcinogenic risks, particularly for children in most samples from group FC. The mean Water Quality Index (WQI) of FC group (156.76 ± 7.30) was significantly higher (p \u3c 0.05) than group FU indicating of its unsuitability. SOM could accurately (80%) predict presence of fluoride in water samples based on other major ions. Sobol sensitivity analysis successfully identified fluoride concentration and body weight as most impactful parameters affecting human health. The integration of advanced modelling techniques and geospatial analysis as Inverse Distance Weightage (IDW) maps has provided a robust framework for ongoing groundwater quality monitoring in mining-affected regions and can help proactive intervention in risk-prone areas. Overall, this comprehensive study takes us a step ahead towards ensuring safe drinking water access for the global community
Dynamic cumulative residual entropy generating function and its properties
No full textIn this work, we study the properties of the cumulative residual entropy generating function (CREGF). We also discuss the non parametric estimation of CREGF. We introduce dynamic cumulative residual entropy generating function (DCREGF). It is shown that the DCREGF determines the distribution uniquely. We study some characterization results using the relationship between DCREGF, hazard rate, and mean residual life function. A new class of life distributions based on decreasing DCREGF is introduced. Finally, we develop a test for decreasing DCREGF and study its performance
Electroosmotic flow modulation and dispersion of uncharged solutes in soft nanochannel
No full textWe perform a systematic study on the modulation of electroosmotic flow (EOF), tuning the selectivity using electrolyte ions and hydrodynamic dispersion of the solute band across the soft nanochannel. The supporting walls of the channel are considered to be hydrophobic and bear non-zero surface charge. For such a channel, the inner side of the supporting rigid walls of the channel are coated with a soft polyelectrolyte layer (PEL). The inhomogeneous distribution of monomers and accompanying volume charge within the PEL is modelled via soft-step function. The dielectric permittivity of the PEL and electrolyte solution are in general different, which in turn leads to the ion partitioning effect. The impact of ion steric effects due to finite sized ions is further accounted through the modified ion activity coefficient. To model the EOF modulation considering the combined impact of the ion steric and ion partitioning effects as well as inhomogeneous distribution of monomers across the PEL, we adopt the modified Poisson-Boltzmann equation as the governing equation for electrostatic potential. The Debye-Bueche model is adopted to study the flow field across the PEL and the Stokes equation governs the EOF outside the PEL. In order to study the impact of the modulated EOF field on the dispersion of uncharged solution, we adopt three different models, i.e., a general 2D convective-diffusion model as well as cross-sectional averaged dispersion models due to Gill and late-time Taylor and Aris. Going beyond the widely employed Debye-Hückel approximation and uniform distribution of the monomer as well as accompanying volume charge, we find the results for the electric double layer (EDL) potential, EOF field and averaged throughput, by tuning the ion selectivity, etc., which is sufficient to analyze the transport of ionized liquid across the channel. The numerical results are supplemented with analytical results for the EDL potential as well as the EOF field under various limiting situations. Besides, we have further shown the impact of the modulated EOF field on the solute dispersion process. We have presented results that highlight the impact of parameters related to EOF field modulation, on solute dispersion governed by a convective-diffusive process, as well as obtaining the results for an effective dispersion coefficient. The dispersion models under the modulated EOF field adopted in the present study can thus be applied to study the dispersion process in engineered microdevices