arXiv subjects

M. S. Hossain

Publications and source records attributed to M. S. Hossain.

5 recordsLinked to original sources

arXiv2026

RGC: a radio AGN classifier based on deep learning. I. A semi-supervised multiclass model for VLA images

Bent radio active galactic nuclei (RAGNs) -- wide-angle tails (WATs) and narrow-angle tails (NATs) -- trace dense environments in galaxy groups and clusters, yet no multiclass classifier simultaneously separates them from straight Fanaroff--Riley types (sFRI, sFRII) using visually inspected labels and unlabelled data. We release FIRST-2060, a four-class labelled dataset of 2060 RAGNs (sFRI, sFRII, WAT, NAT) constructed from three publicly available catalogues through multi-tier visual inspection, together with the semi-supervised RGC 1.0 model that leverages 20,000 unlabelled sources. We benchmark RGC against five supervised baselines. FIRST-2060 is provided in two preprocessing variants: $\mathbf{R}_{L1}$, which retains spurious sources, and $\mathbf{R}_{L2}$, from which they are removed. The RGC model integrates the self-supervised framework BYOL (Bootstrap Your Own Latent) with an $E(2)$-equivariant steerable CNN (E2CNN) encoder, pre-trained on the unlabelled data and fine-tuned on the labelled sets. All six models are evaluated with 5-fold cross-validation, Grad-CAM attention analysis, and controlled class-imbalance experiments. ConvNeXT ($M_1$) and RGC ($M_2$) form a top tier at macro-$F_1$ $0.80\pm0.02$ and $0.79\pm0.02$ respectively, a difference within one standard deviation. $M_2$ is the only model whose Grad-CAM contours consistently trace the morphological structure of RAGNs -- lobes, jets, and bends -- rather than defaulting to compact blobs or diffuse patterns. The four-class scheme introduced here enables WAT/NAT-resolved catalogues that can serve as environment probes and progenitor classifications for diffuse cluster radio emission. The complementary strengths of $M_1$ and $M_2$ -- in cross-type and within-type discrimination respectively -- suggest that an ensemble approach may offer a practical framework for survey-scale morphological catalogues.

astro-ph.IM↗

arXiv2022

High pressure mediated physical properties of Hf2AB (A = Pb, Bi) via DFT calculations

Using density functional theory (DFT), the structural, mechanical, electronic, thermal, and optical properties of Hf2AB (A = Pb, Bi) borides were studied, considering the pressure effect up to 50 GPa. The lattice constants were found to be decreased with increasing pressure wherein the lattice constants at 0 GPa agree well with the reported values. The stability (mechanical and dynamical) of the titled compounds at different pressures was checked. The mechanical behavior was disclosed considering the bulk modulus, shear modulus, Youngs modulus, Pugh ratio, Poissons ratio, and hardness parameter at different pressures. Pugh and Poisson ratios were used to assess the brittleness and ductility of the titled borides. The anisotropic nature of mechanical properties was studied by calculating different indices and plotting 2D and 3D projections of the elastic moduli. The electronic properties were revealed by calculating the band structure, density of states, and charge density mapping at different pressures, wherein the anisotropic nature of the electronic conductivity was noted. We studied the Debye temperature, minimum thermal conductivity, Gruneisen parameter, and melting temperature of the titled borides at different pressures; the results revealed the improvement of the mentioned properties with rising pressure. The important optical constants to disclose the possible relevance in application purposes were investigated; a little pressure effect was noted. The thermal properties suggest that the titled borides could be used as thermal barrier coating (TBC) materials while the reflectivity spectra revealed their suitability to be used as cover materials for protection from solar heating.

cond-mat.mtrl-sci↗

arXiv2021

Physical properties of predicted MAX phase borides Hf2AB (A = Pb, Bi): a DFT insight

We have used density functional theory to study the recently predicted MAX phase borides Hf2AB (A = Pb, Bi) in where the mechanical, electronic, thermal, and optical properties have been investigated for the first time. A good agreement of the obtained lattice constants with the reported values confirmed the well accuracy of the present calculations. The stiffness constants (Cij) attest to the mechanical stability of all title compounds. The mechanical behaviors have been scrutinized discreetly by considering the bulk modulus, shear modulus, Youngs modulus, as well as hardness parameters. The brittle nature of Hf2AB (A = Pb, Bi) borides has also been confirmed. The electronic band structure and density of states (DOS) revealed the metallic behavior of the titled materials. The anisotropy in electrical conductivity has been disclosed by considering the energy dispersion along different directions. The variation of Vickers hardness is explained in terms of the total DOS of Hf2AB (A = Pb, Bi). The anisotropic nature of the mechanical properties of the phases has also been studied. The technologically important parameters (Debye temperature, minimum thermal conductivity, and Grüneisen parameter) have also been used to evaluate the thermal behaviors of the titled materials. The possibility of Hf2AB (A = Pb, Bi) for use as coating materials has been assessed by studying the reflectivity.

cond-mat.mtrl-sci↗

arXiv2020

Energy Efficiency and Hover Time Optimization in UAV-based HetNets

In this paper, we investigate the downlink performance of a three-tier heterogeneous network (HetNet). The objective is to enhance the edge capacity of a macro cell by deploying unmanned aerial vehicles (UAVs) as flying base stations and small cells (SCs) for improving the capacity of indoor users in scenarios such as temporary hotspot regions or during disaster situations where the terrestrial network is either insufficient or out of service. UAVs are energy-constrained devices with a limited flight time, therefore, we formulate a two layer optimization scheme, where we first optimize the power consumption of each tier for enhancing the system energy efficiency (EE) under a minimum quality-of-service (QoS) requirement, which is followed by optimizing the average hover time of UAVs. We obtain the solution to these nonlinear constrained optimization problems by first utilizing the Lagrange multipliers method and then implementing a sub-gradient approach for obtaining convergence. The results show that through optimal power allocation, the system EE improves significantly in comparison to when maximum power is allocated to users (ground cellular users or connected vehicles). The hover time optimization results in increased flight time of UAVs thus providing service for longer durations.

eess.SP↗

arXiv2019

Prostate Segmentation from Ultrasound Images using Residual Fully Convolutional Network

Medical imaging based prostate cancer diagnosis procedure uses intra-operative transrectal ultrasound (TRUS) imaging to visualize the prostate shape and location to collect tissue samples. Correct tissue sampling from prostate requires accurate prostate segmentation in TRUS images. To achieve this, this study uses a novel residual connection based fully convolutional network. The advantage of this segmentation technique is that it requires no pre-processing of TRUS images to perform the segmentation. Thus, it offers a faster and straightforward prostate segmentation from TRUS images. Results show that the proposed technique can achieve around 86% Dice Similarity accuracy using only few TRUS datasets.

cs.CV↗