arXiv subjects

M. M. Rahman

Publications and source records attributed to M. M. Rahman.

15 recordsLinked to original sources

arXiv2025

First-Principles Investigation of Mechanical, Lattice Dynamical, and Thermodynamic Properties of BaTiO3 Polymorphs

BaTiO3 (BTO) is one of the most interesting classes of perovskite materials. The present study has been complied to explore some physical properties such as mechanical, vibrational, thermo-physical, and temperature dependent thermodynamic properties of BaTiO3 polymorphs comprehensively using first principles calculations based on density functional theory (DFT). All the polymorphs are found to be mechanically stable. The polymorphs are elastically anisotropic, machinable and have high hardness and toughness. The cubic phase possesses brittle nature while the other phases show ductile character. The high melting point of the polymorphs reveals that they can be used in tough situations. Also, three of the polymorphs can be used as thermal barrier coating. Moreover, we have also calculated the lattice dynamics and found improved results compared to the available results in the literature. In addition, the temperature and pressure dependent thermodynamic parameters of the polymorphs are evaluated and analyzed for the first time using the quasi-harmonic Debye model. The thermodynamic properties suggested that all phases would be good choices for application in the fields of automobiles, cooling systems, thermal electronic devices, thermal exchangers, and space crafts.

cond-mat.mtrl-sci↗

arXiv2025

Physical and chemical characterization of Saccharum spontaneum flower fibre: potential applications in thermal insulation and microbial fuel cells

Saccharum spontaneum is a grass-type plant abundantly found in the Indian subcontinent, known for its beautiful, lustrous white flowers. Fibres were extracted from the flower and analyzed for their physical, mechanical, and chemical properties. The chemical composition of the fibre is 90.9% holocellulose, with a moisture content of 10.97%, and an average fibre length of 25 mm. FTIR spectra confirmed the presence of functional groups similar to those found in other natural cellulosic fibres. Additionally, the fibre exhibits a tensile strength of approximately 63 cN/tex, which is significantly higher than that of cotton and jute fibres. However, its crystallinity is relatively high at about 75%, resulting in a low elongation at break of 1.9%. FESEM analysis revealed a hollow structure in the fibre, indicating its potential suitability for applications requiring high thermal insulation, excellent moisture management, vapor permeability, and microbial fuel cell development.

physics.bio-ph↗

arXiv2024

AI-Driven Smartphone Solution for Digitizing Rapid Diagnostic Test Kits and Enhancing Accessibility for the Visually Impaired

Rapid diagnostic tests are crucial for timely disease detection and management, yet accurate interpretation of test results remains challenging. In this study, we propose a novel approach to enhance the accuracy and reliability of rapid diagnostic test result interpretation by integrating artificial intelligence (AI) algorithms, including convolutional neural networks (CNN), within a smartphone-based application. The app enables users to take pictures of their test kits, which YOLOv8 then processes to precisely crop and extract the membrane region, even if the test kit is not centered in the frame or is positioned at the very edge of the image. This capability offers greater accessibility, allowing even visually impaired individuals to capture test images without needing perfect alignment, thus promoting user independence and inclusivity. The extracted image is analyzed by an additional CNN classifier that determines if the results are positive, negative, or invalid, providing users with the results and a confidence level. Through validation experiments with commonly used rapid test kits across various diagnostic applications, our results demonstrate that the synergistic integration of AI significantly improves sensitivity and specificity in test result interpretation. This improvement can be attributed to the extraction of the membrane zones from the test kit images using the state-of-the-art YOLO algorithm. Additionally, we performed SHapley Additive exPlanations (SHAP) analysis to investigate the factors influencing the model's decisions, identifying reasons behind both correct and incorrect classifications. By facilitating the differentiation of genuine test lines from background noise and providing valuable insights into test line intensity and uniformity, our approach offers a robust solution to challenges in rapid test interpretation.

cs.CV↗

arXiv2024

Exploring the effects of diameter and volume fraction of quantum dots on photocarrier generation rate in solar cells

This paper extends a previous model for p-i-n GaAs quantum dot solar cells (QDSC) by revising the equation of photocarrier generation rate in quantum dots (QDs) inside the intrinsic region. In our model, we address a notable discrepancy that arose from the previous model where they did not consider the volume of QDs within the intrinsic region, leading to an overestimation of the photocarrier generation rate. Our present model rectifies this by incorporating the volume of quantum dots, resulting in adjustments to the photocarrier generation rate. Additionally, we determine the absorption coefficient of the QDs based on Mie theory for different diameter sizes considering the constant volume fraction of the total number of QDs in the intrinsic region. We observe in our analysis that the absorption spectra of the QDs and host material may overlap in certain cases, although the previous model assumed no overlap. This finding suggests the need for caution when evaluating spectral overlap: if the spectra do not overlap, both the previous and current modified models can be reliably applied. However, in cases of overlap, careful consideration is required to ensure accurate predictions of photocarrier generation. Furthermore, investigating the effect of QD diameter size on the photocarrier generation rate in the intrinsic region, we find that smaller QD sizes result in a higher absorption coefficient as well as a higher generation rate for a constant volume of QDs in the region. Moreover, we establish the optimization of the QDs array size by varying the size and the total volume of QDs to improve the generation rate. Our analysis reveals that a higher volume of QDs and a smaller size of QDs result in the maximum generation rate. From an experimental perspective, we propose that the optimal arrangement of QDs in such solar cells is a 0.5 volume fraction with a QD diameter of 2 nm.

physics.app-ph↗

arXiv2024

The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting

A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition time series typically starts with an already pathological scan. This poses problems, as many algorithms are designed to analyze healthy brains and provide no guarantee for images featuring lesions. Examples include, but are not limited to, algorithms for brain anatomy parcellation, tissue segmentation, and brain extraction. To solve this dilemma, we introduce the BraTS inpainting challenge. Here, the participants explore inpainting techniques to synthesize healthy brain scans from lesioned ones. The following manuscript contains the task formulation, dataset, and submission procedure. Later, it will be updated to summarize the findings of the challenge. The challenge is organized as part of the ASNR-BraTS MICCAI challenge.

eess.IV↗

arXiv2023

Enhancing the Stretchability of Two-Dimensional Materials through Kirigami: A Molecular Dynamics Study on Tungsten Disulfide

In recent years, the 'kirigami' technique has gained significant attention for creating meta-structures and meta-materials with exceptional characteristics, such as unprecedented stretchability. These properties, not typically inherent in the original materials or structures, present new opportunities for applications in stretchable electronics and photovoltaics. However, despite its scientific and practical significance, the application of kirigami patterning on a monolayer of tungsten disulfide (WS2), a van der Waals material with exceptional mechanical, electronic, and optical properties, has remained unexplored. This study utilizes molecular dynamics (MD) simulations to investigate the mechanical properties of monolayer WS2 with rectangular kirigami cuts. We find that, under tensile loading, the WS2 based kirigami structure exhibits a notable increase in tensile strain and a decrease in strength, thus demonstrating the effectiveness of the kirigami cutting technique in enhancing the stretchability of monolayer WS2. Additionally, increasing the overlap ratio enhances the stretchability of the structure, allowing for tailored high strength or high strain requirements. Furthermore, our observations reveal that increasing the density of cuts and reducing the length-to-width ratio of the kirigami nanosheet further improve the fracture strain, thereby enhancing the overall stretchability of the proposed kirigami patterned structure of WS2.

physics.comp-ph↗

arXiv2022

Structural, Dielectric, and Electrical Transport Properties of Al3+ Substituted Nanocrystalline Ni-Cu Spinel Ferrites Prepared Through the Sol-Gel Route

In this study, a series of nanocrystalline ferrites of Ni0.7Cu0.30AlxFe2-xO4 (x=0.00 to 0.10 with a step of 0.02) has been synthesized through the sol-gel auto combustion technique. The structural, morphological, dielectric, and electrical properties of the Ni-Cu spinel ferrite nanoparticles are analyzed due to the substitution of Al3+ content. The crystalline and structural characteristics of the prepared nanoparticles (NPs) have been studied employing the x-ray diffraction (XRD) spectra and FTIR analysis. The extracted XRD patterns assure the single-phase cubic spinel structure of all samples with homogeneity and no impurity, which indicates the yielding of high crystalline NPs. A slight decrease of average grain size with increment of Al3+ content is observed in the surface morphological study carried out by the field emission scanning electron microscopy (FESEM). The studied materials are found in semi-spherical shapes, showing the multi-domain grains separated by grain boundaries with some agglomerations. The chemical composition study for the synthesized NI-Cu spinel ferrites using energy dispersive x-ray (EDX) ensures the presence of each component in appropriate proportions in each sample.

cond-mat.mtrl-sci↗

arXiv2021

Effect of Kinematics and Fluency in Adversarial Synthetic Data Generation for ASL Recognition with RF Sensors

RF sensors have been recently proposed as a new modality for sign language processing technology. They are non-contact, effective in the dark, and acquire a direct measurement of signing kinematic via exploitation of the micro-Doppler effect. First, this work provides an in depth, comparative examination of the kinematic properties of signing as measured by RF sensors for both fluent ASL users and hearing imitation signers. Second, as ASL recognition techniques utilizing deep learning requires a large amount of training data, this work examines the effect of signing kinematics and subject fluency on adversarial learning techniques for data synthesis. Two different approaches for the synthetic training data generation are proposed: 1) adversarial domain adaptation to minimize the differences between imitation signing and fluent signing data, and 2) kinematically-constrained generative adversarial networks for accurate synthesis of RF signing signatures. The results show that the kinematic discrepancies between imitation signing and fluent signing are so significant that training on data directly synthesized from fluent RF signers offers greater performance (93% top-5 accuracy) than that produced by adaptation of imitation signing (88% top-5 accuracy) when classifying 100 ASL signs.

eess.SP↗

arXiv2019

Learnt dynamics generalizes across tasks, datasets, and populations

Differentiating multivariate dynamic signals is a difficult learning problem as the feature space may be large yet often only a few training examples are available. Traditional approaches to this problem either proceed from handcrafted features or require large datasets to combat the m >> n problem. In this paper, we show that the source of the problem---signal dynamics---can be used to our advantage and noticeably improve classification performance on a range of discrimination tasks when training data is scarce. We demonstrate that self-supervised pre-training guided by signal dynamics produces embedding that generalizes across tasks, datasets, data collection sites, and data distributions. We perform an extensive evaluation of this approach on a range of tasks including simulated data, keyword detection problem, and a range of functional neuroimaging data, where we show that a single embedding learnt on healthy subjects generalizes across a number of disorders, age groups, and datasets.

cs.CV↗

arXiv2017

On entropy, specific heat, susceptibility and Rushbrooke inequality in percolation

We investigate percolation, a probabilistic model for continuous phase transition (CPT), on square and weighted planar stochastic lattices. In its thermal counterpart, entropy is minimally low where order parameter (OP) is maximally high and vice versa. Besides, specific heat, OP and susceptibility exhibit power-law when approaching the critical point and the corresponding critical exponents $α, β, γ$ respectably obey the Rushbrooke inequality (RI) $α+2β+γ\geq 2$. Their analogues in percolation, however, remain elusive. We define entropy, specific heat and redefine susceptibility for percolation and show that they behave exactly in the same way as their thermal counterpart. We also show that RI holds for both the lattices albeit they belong to different universality classes.

cond-mat.stat-mech↗

arXiv2017

Solitary waves and double layers in an adiabatic multi-component space plasma

The formation and propagation of small amplitude Heavy-ion-acoustic (HIA) solitary waves and double layers in an unmagnetized collisionless multi-component plasma system consisting of superthermal electrons, Boltzmann distributed light ions, and adiabatic positively charged inertial heavy ions are theoretically investigated. The reductive perturbation technique is employed to derive the modified Korteweg-de Vries (mK-dV) and standard Gardner (SG) equations. The solitary wave (SW) solution of mK-dV and SG equations as well as Double Layers (DLs) solution of SG equation is studied for analysis of higher-order nonlinearity. It is found that the plasma system under consideration supports positive and negative potential Gardner solitons but only positive potential mK-dV solitons. In addition, it is shown that, the basic properties of HIA mK-dV and Gardner solitons and DLs (viz. polarity, amplitude, width, and phase speed) are incomparably influenced by the adiabaticity effect of heavy ions and the superthermality effect of electrons. The relevance of the present findings to the system of space plasmas as well as to the system of researchers interest is specified.

physics.plasm-ph↗

arXiv2016

Explosive percolation on scale-free multifractal weighted planar stochastic lattice

In this article, we investigate explosive bond percolation (EBP) with product rule, formally known as Achlioptas process, on a scale-free multifractal weighted planar stochastic lattice (WPSL). One of the key features of the EBP transition is the delay, compared to corresponding random bond percolation (RBP), in the onset of spanning cluster. However, when it happens, it happens so dramatically that initially it was believed, albeit ultimately proved wrong, that explosive percolation (EP) exhibits first order transition. In the case of EP, much efforts were devoted to resolving the issue of its order of transition and almost no effort being devoted to find critical point, critical exponents etc., to classify it into universality classes. This is in sharp contrast to the classical random percolation. We do not even know all the exponents of EP for regular planar lattice or for Erdös-Renyi network. We first find numerically the critical point $p_c$ and then obtain all the critical exponents $β, γ, ν$ as well as the Fisher exponent $τ$ and the fractal dimension $d_f$ of the spanning cluster. We also compare our results for EBP with those of the RBP and find that all the exponents of EBP obeys the same scaling relations as do the RBP. Our findings suggests that EBP is no special except the fact that the exponent $β$ is unusually small compared to that of RBP.

cond-mat.stat-mech↗

arXiv2016

Universality class of site and bond percolation on multi-multifractal scale-free planar stochastic lattice

In this article, we investigate both site and bond percolation on a weighted planar stochastic lattice (WPSL) which is a multi-multifractal and whose dual is a scale-free network. The characteristic properties of percolation is that it exhibits threshold phenomena as we find sudden or abrupt jump in spanning probability across $p_c$ accompanied by the divergence of some other observable quantities which is reminiscent of continuous phase transition. Indeed, percolation is characterized by the critical behavior of percolation strength $P(p)\sim (p_c-p)^β$, mean cluster size $S\sim (p_c-p)^{-γ}$ and the system size $L\sim (p_c-p)^{-ν}$ which are known as the equivalent counterpart of the order parameter, susceptibility and correlation length respectively. Moreover, the cluster size distribution function $n_s(p_c)\sim s^{-τ}$ and the mass-length relation $M\sim L^{d_f}$ of the spanning cluster also provide useful characterization of the percolation process. We obtain an exact value for $p_c$ and for all the exponents such as $β, ν, γ, τ$ and $d_f$. We find that, except $p_c$, all the exponents are exactly the same in both bond and site percolation despite the significant difference in the definition of cluster and other quantities. Our results suggest that the percolation on WPSL belongs to a new universality class as its exponents do not share the same value as for all the existing planar lattices and like other cases its site and bond belong to the same universality class.

cond-mat.stat-mech↗

arXiv2015

New universality class in percolation on multifractal scale-free planar stochastic lattice

We investigate site percolation on a weighted planar stochastic lattice (WPSL) which is a multifractal and whose dual is a scale-free network. Percolation is typically characterized by percolation threshold $p_c$ and by a set of critical exponents $β$, $γ$, $ν$ which describe the critical behavior of percolation probability $P(p)\sim (p_c-p)^β$, mean cluster size $S\sim (p_c-p)^{-γ}$ and the correlation length $ξ\sim (p_c-p)^{-ν}$. Besides, the exponent $τ$ characterizes the cluster size distribution function $n_s(p_c)\sim s^{-τ}$ and the fractal dimension $d_f$ the spanning cluster. We obtain an exact value for $p_c$ and for all these exponents. Our results suggest that the percolation on WPSL belong to a new universality class as its exponents do not share the same value as for all the existing planar lattices.

cond-mat.stat-mech↗

arXiv2010

Analysis of Large Scale Propagation Models for Mobile Communications in Urban Area

Channel properties influence the development of wireless communication systems. Unlike wired channels that are stationary and predictable, radio channels are extremely random and dont offer easy analysis. A Radio Propagation Model (RPM), also known as the Radio Wave Propagation Model (RWPM), is an empirical mathematical formulation for the characterization of radio wave propagation as a function of frequency. In mobile radio systems, path loss models are necessary for proper planning, interference estimations, frequency assignments and cell parameters which are the basic for network planning process as well as Location Based Services (LBS) techniques. Propagation models that predict the mean signal strength for an arbitrary transmitter receiver (T R) separation distance which is useful in estimating the radio coverage area of a transmitter are called large scale propagation models, since they characterize signal strength over large TR separation distances. In this paper, the large scale propagation performance of Okumura, Hata, and Lee models has been compared varying Mobile Station (MS) antenna height, Transmitter Receiver (TR) distance and Base Station (BS) antenna height, considering the system to operate at 900 MHz. Through the MATLAB simulation it is turned out that the Okumura model shows the better performance than that of the other large scale propagation models.

cs.NI↗