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Priyanka Sinha

Publications and source records attributed to Priyanka Sinha.

At least 19 recordsLinked to original sources

Structured Gossip: A Partition-Resilient DNS for Internet-Scale Dynamic Networks

Network partitions pose fundamental challenges to distributed name resolution in mobile ad-hoc networks (MANETs) and edge computing. Existing solutions either require active coordination that fails to scale, or use unstructured gossip with excessive overhead. We present \textit{Structured Gossip DNS}, exploiting DHT finger tables to achieve partition resilience through \textbf{passive stabilization}. Our approach reduces message complexity from $O(n)$ to $O(n/\log n)$ while maintaining $O(\log^2 n)$ convergence. Unlike active protocols requiring synchronous agreement, our passive approach guarantees eventual consistency through commutative operations that converge regardless of message ordering. The system handles arbitrary concurrent partitions via version vectors, eliminating global coordination and enabling billion-node deployments.

cs.NI

Early Warning From Eccentric Compact Binaries: Template Initialization And Sub-dominant Mode Effects

Early warning of gravitational waves (GWs) is essential for multi-messenger observations of binary neutron star and black hole-neutron star merger events. In this study, we investigate early warning prospects from eccentric compact binaries, whose mergers are expected to comprise a significant fraction of detected GW events in the future. Eccentric binaries exhibit oscillatory frequency evolution, causing GW frequencies to recur multiple times through their coalescence. Consequently, generating eccentric waveform templates for early warning requires specification of initial conditions. While the standard approach involves initiating waveform generation when the orbit-averaged frequency enters the detector band, we compare this with an alternative approach that uses the periastron frequency as the starting point. Our analysis shows that initializing at the periastron frequency yields an improved signal-to-noise ratio and sky localization. Additionally, including subdominant modes alongside the dominant $(2,2)$ mode leads to further improvements in sky localization. We explore the parameter space of primary mass $m_1 \in [1.4, 15] \, M_\odot$, spin $\chi_1 \in [0, 0.8]$, and eccentricity $e \leq 0.4$ across three detector configurations: O5, Voyager, and 3G. We find that in the O5 (Voyager) configuration, including eccentricity and subdominant modes, the sky localization area can be reduced by $2-80\% (2-85\%)$ at 1000 sq. deg. with increasing eccentricity from $e_5 = 0.1$ to $e_5 = 0.4$, yielding up to $41$ seconds (1 minute) of extra early warning time. For NSBH systems, subdominant modes contribute up to $70$ $(94)\%$ reduction for O5 (Voyager) scenario. In the 3G detector scenario, the sky area reduction due to eccentricity reaches $80\%$ (from $e_{2.5} = 0.1$ to $e_{2.5} = 0.4$) at 100 sq. deg., and subdominant modes enhance the reduction up to $98\%$ for NSBH systems.

gr-qc

Magneto transport of pressure induced flatbands in large angle twisted bilayer graphene

Twisted bilayer graphene (TBG) exhibits flat electronic bands at the so-called magic angle ($\sim 1.1^\circ$), leading to strong electron correlations and emergent quantum phases such as superconductivity and correlated insulating states. However, beyond the magic angle, the band structure generally remains dispersive, diminishing interaction-driven phenomena. In this work, we explore the equivalence between pressure-induced flatbands and the magic-angle flatband in large-angle TBG by systematically analyzing the role of interlayer coupling modifications under perpendicular pressure. We show that pressure-induced flatbands exhibit spatial localization similar to magic-angle TBG, with charge density concentrated in the AA-stacked regions. Furthermore, the Hall conductivity and magneto-transport properties under an external magnetic field reveal that these pressure-induced flatbands share key signatures with the quantum Hall response of magic-angle TBG. The obtained Hofstadter spectrum shows four consistent low-energy gaps across all twist angles under pressure, which align with the calculated Hall conductivity plateaus. Our findings suggest that pressure offers an alternative pathway to engineer flat electronic bands and correlated states in TBG, extending the landscape of tunable moiré materials beyond the constraints of the magic angle.

cond-mat.mes-hall

Strain induced tunable band gap and optical properties of graphene on hexagonal boron nitride

In this study, we highlight the potential of strain engineering in graphene/hBN (hexagonal Boron nitride) 2D heterostructures, enabling their use as wide-range light absorbers with significant implications for optoelectronic applications. We systematically investigate the electronic and optical properties of graphene/hBN under the application of strain, considering various stacking geometries within the framework of density-functional theory. The semimetallic graphene layer upon aligning on the insulating hexagonal boron nitride sheet opens a few tens of meV band gap at the Dirac point due to the induced on-site energy differences on the two sublattices of graphene. Here, we demonstrate that by simultaneously tuning the interlayer distance and lattice constant, this band gap can be significantly increased to 1 eV. Interestingly, in both scenarios (small and large band gaps), the material undergoes a transition from a semiconductor to a semimetallic state. Importantly, the tunability of this band gap is strongly influenced by the specific stacking configuration. We further explored the optical properties across a broad spectrum, revealing that the presence of a strain-induced band gap fundamentally alters how light interacts with the system.

cond-mat.mes-hall

Magnetotransport properties of a twisted bilayer graphene in the presence of external electric and magnetic field

We extensively investigate the electronic and transport properties of a twisted bilayer graphene when subjected to both an external perpendicular electric field and a magnetic field. Using a basic tight-binding model, we show the flat electronic band properties as well as the density of states (DOS), both without and with the applied electric field. In the presence of an electric field, the degeneracy at the Dirac points is lifted where the non-monotonic behavior of the energy gap exists, especially for twist angles below 3$^\circ$. We also study the behavior of the Landau levels (LL) spectra for different twist angles within a very low energy range. These LL spectra get modified under the influence of the external electric field. Moreover, we calculate the dc Hall conductivity ($σ_{xy}$) for a very large system using the Kernel Polynomial Method (KPM). Interestingly, $σ_{xy}$ makes a transition from a half-integer to an integer quantum Hall effect, \textit{i.e.} the value of $σ_{xy}$ shifts from $\pm 4(n+1/2) (2e^2/h)$ ($n$ is an integer) to $\pm 2n (2e^2/h)$ around a small twist angle of $θ=2.005^\circ$. At this angle, $σ_{xy}$ acquires a Hall plateau at zero Fermi energy. However, the behavior of $σ_{xy}$ remains unaltered when the system is exposed to the electric field, particularly at the magic angle where the bands in both layers can hybridize and strong interlayer coupling plays a crucial role.

cond-mat.mes-hall

Fusing machine learning strategy with density functional theory to hasten the discovery of MXenes for hydrogen generation

The complexity of the topological and combinatorial configuration space of MXenes can give rise to gigantic design challenges that cannot be addressed through traditional experimental or routine theoretical approaches. To this end, we establish a robust and more broadly applicable multistep workflow from the toolbox of supervised machine learning (ML) algorithms for predicting the hydrogen evolution reaction (HER) activity over 4,500 MM$^{\prime}$XT$_2$-type MXenes, where 25\% of the material space (1125 systems) is randomly selected to evaluate the HER performance using density functional theory (DFT) calculations. As the most desirable ML model, the random forest regression method with recursive feature elimination and hyperparameter optimization accurately and rapidly predicts the Gibbs free energy of hydrogen adsorption ($Δ$G$_{H}$) with a low predictive mean absolute error of 0.374 eV. Based on these observations, the H-atom adsorbed directly on top of the outermost metal atomic layer of the MM$^{\prime}$XT$_2$-type MXenes (site-2) with Nb, V, Mo, Cr and Ti metals composed of carbon based O-functionalization are discovered to be highly stable and active catalysts, surpassing that of commercially available platinum based counterparts. Overall, the physically meaningful predictions and insights of the developed ML/DFT-based multistep workflow will open new avenues for accelerated screening, rational design and discovery of potential HER catalysts.

cond-mat.mtrl-sci

Digital Literacy and Reading Habits of The DMI-St. Eugene University Students

Digital literacy is the skill of finding, evaluating, consuming, and generating information using digital technologies. The study attempted to comprehend university students' digital reading habits and skills. It also provides a glimpse of the pupils' favorite reading materials, including physical and digital sources. We examined BSc and BE Computer Science students of DMI-St. Eugene University, Zambia. The tool was a structured questionnaire that was distributed through WhatsApp. The study's findings revealed that most students thoroughly understand digital tools and how to use them but lack the skills to build their websites and portfolio. Out of 115 students, all agreed they used computers for learning purposes. Usage of digital environments, generally, they used the World Wide Web for searching for information. Additionally, most students have medium digital application skills, despite their preference for reading electronic books. The results indicate that students' gender and level of education had a statistically significant link with their digital literacy, whereas age wasn't shown to be a statistically relevant predictor. The findings show that, in terms of education, especially reading, students' or readers' top priorities are electronic resources; print book preferences are reduced.

cs.CY

Research Data Management and Services in South Asian Academic Libraries

The study examined the research data management and related services offered by South Asian countries' academic libraries. Research applied quantitative approach and survey research design method were used for this study. The survey questionnaire was distributed randomly to academic library professionals in five countries: Afghanistan, Bangladesh, India, Pakistan, and Sri Lanka. The sample population comprised 67 library professionals from various institutes of five countries. The study recommends that institutes or funding organizations support staff to attend conferences and workshops on research data management, library professionals have to join MOOC to take courses related to research data services, Institute or professionals conduct in-house staff workshops and presentations. The study also found that 64.2 per cent agreed compliance with funder requirements and preservation are major issues.

cs.CY

Digital Literacy and Reading Habits of the Central University of Tamil Nadu Students: A Survey Study

The study attempted to understand the University students' digital reading habits and their related skills. It also has a view of students' preferred sources of reading, whether physical or digital resources. For this study, we conducted a survey study with students and research scholars of the Central University of Tamil Nadu, India. The instrument was a structured questionnaire distributed with various modes. The result found that the majority of the students are well known about digital tools and usage, most of the students are excellent in digital literacy skills and other findings is however they are good in digital literacy even though they like to read print books is their most favorable preference. The results conclude that whatever technological devices are developed and students have also grown their technical knowledge. The result finds out, in education especially reading-wise, students or readers' first wish is printed resources; digital books are secondary to them.

cs.DL

Library and Information Science Scholarly Journals Publishing Simulation: A Study

The author's productivity is assessed based on publications, which requires a lot of motivation and time. Manuscripts get through several steps before being accepted and published. The purpose of this paper is to understand the time gap between acceptance to the publication of manuscripts in reputed journals of Library and Information Science. This paper is useful to contemporary researchers for knowing the journal publication duration. In this paper, we discussed the refereed and index journals in the field of library and information science. For this study, we collected the data from six LIS journals which were published from the 2020 January to December Asian region. The study focuses on detailed analyses of journal processing and publishing duration. The major contribution of this study gives the six LIS journal processing time they are: author manuscript submitted to accepted, accepted to published, and submitted to published period.

cs.DL

Mobility State Detection of Cellular-Connected UAVs based on Handover Count Statistics

To ensure reliable and effective mobility management for aerial user equipment (UE), estimating the speed of cellular-connected unmanned aerial vehicles (UAVs) carries critical importance since this can help to improve the quality of service of the cellular network. The 3GPP LTE standard uses the number of handovers made by a UE during a predefined time period to estimate the speed and the mobility state efficiently. In this paper, we introduce an approximation to the probability mass function of handover count (HOC) as a function of a cellular-connected UAV's height and velocity, HOC measurement time window, and different ground base station (GBS) densities. Afterward, we derive the Cramer-Rao lower bound (CRLB) for the speed estimate of a UAV, and also provide a simple biased estimator for the UAV's speed which depends on the GBS density and HOC measurement period. Interestingly, for a low time-to-trigger (TTT) parameter, the biased estimator turns into a minimum variance unbiased estimator (MVUE). By exploiting this speed estimator, we study the problem of detecting the mobility state of a UAV as low, medium, or high mobility as per the LTE specifications. Using CRLBs and our proposed MVUE, we characterize the accuracy improvement in speed estimation and mobility state detection as the GBS density and the HOC measurement window increase. Our analysis also shows that the accuracy of the proposed estimator does not vary significantly with respect to the TTT parameter.

eess.SP

Wireless Connectivity and Localization for Advanced Air Mobility Services

By serving as an analog to traffic signal lights, communication signaling for drone to drone communications holds the key to the success of advanced air mobility (AAM) in both urban and rural settings. Deployment of AAM applications such as air taxis and air ambulances, especially at large-scale, requires a reliable channel for a point-to-point and broadcast communication between two or more aircraft. Achieving such high reliability, in a highly mobile environment, requires communication systems designed for agility and efficiency. This paper presents the foundations for establishing and maintaining a reliable communication channel among multiple aircraft in unique AAM settings. Subsequently, it presents concepts and results on wireless coverage and mobility for AAM services using cellular networks as a ground network infrastructure. Finally, we analyze the wireless localization performance at 3D AAM corridors when cellular networks are utilized, considering different corridor heights and base station densities. We highlight future research directions and open problems to improve wireless coverage and localization throughout the manuscript.

eess.SP

Magneto-optical properties of a semi-Dirac nanoribbon in the terahertz frequency regime

We study magneto-optical (MO) properties of a semi-Dirac nanoribbon in presence of a perpendicular magnetic field using Kernel Polynomial Method (KPM) based on the Keldysh formalism in the experimental (terahertz frequency) regime. For comparison, we have also included results for the Dirac systems as well, so that the interplay of the band structure deformation and MO conductivities can be studied. We have found that the MO conductivity shows features in the semi-Dirac system that are quite distinct from the Dirac case near the ultra-violet and the visible regimes. The real parts of the longitudinal conductivities, namely Re($σ_{xx}$) and Re($σ_{yy}$) (which are different in the semi-Dirac case, as opposed to a Dirac one) present a series of resonance peaks as a function of the incident photon energy. We have also found that the absorption peaks corresponding to the $y$-direction are larger (roughly one order of magnitude) than those corresponding to the $x$-direction for the semi-Dirac case. In the case of the Hall conductivity, that is, Re($σ_{xy}$), there are extra peaks in the spectra compared to the Dirac case which originate from the distinct optical transitions of the carriers from one Landau level to another. We have also explored how the carrier concentration influences the MO conductivities. In the semi-Dirac case, there is the emergence of additional peaks yet again in the absorption spectrum underscoring the presence of an asymmetric dispersion compared to the Dirac case. Further, we have explored the interplay between the polarization of the incident beam and the features of the absorption spectra which can be probed in experiments. Finally, we evaluate the MO activity of the medium by computing the Faraday rotation angle, $θ_{F}$.

cond-mat.mes-hall

Explaining Outcomes of Multi-Party Dialogues using Causal Learning

Multi-party dialogues are common in enterprise social media on technical as well as non-technical topics. The outcome of a conversation may be positive or negative. It is important to analyze why a dialogue ends with a particular sentiment from the point of view of conflict analysis as well as future collaboration design. We propose an explainable time series mining algorithm for such analysis. A dialogue is represented as an attributed time series of occurrences of keywords, EMPATH categories, and inferred sentiments at various points in its progress. A special decision tree, with decision metrics that take into account temporal relationships between dialogue events, is used for predicting the cause of the outcome sentiment. Interpretable rules mined from the classifier are used to explain the prediction. Experimental results are presented for the enterprise social media posts in a large company.

cs.AI

Quantum Hall studies of a Semi-Dirac Nanoribbon

Here we comprehensively investigate Landau levels, Hofstadter butterfly and transport properties of a semi-Dirac nanoribbon in a perpendicular magnetic field using a recently developed real-space implementation of the Kubo formula based on Kernel Polynomial Method. A Dirac ribbon is considered to compare and contrast our results for a semi-Dirac system. We find that the Landau levels being non-equidistant from each other for the semi-Dirac case (true for a Dirac as well), the flatness of the energy bands vanishes in the bulk and becomes dispersive for a semi-Dirac ribbon in contrast to a Dirac system. This feature is most discernible for intermediate values of the external field. We further compute the longitudinal ($σ_{xx}$ and $σ_{yy}$) and the transverse or Hall ($σ_{xy}$) conductivities where the Hall conductivity shows a familiar quantization, namely, $σ_{xy} \propto 2n$ (the factor `2' includes the spin degeneracy) which is highly distinct from a Dirac system, such as graphene. We also observe anisotropic behavior in magneto-transport in a semi-Dirac ribbon owing to the dispersion anomalies in two different longitudinal directions. Our studies may have important ramifications for monolayer phosphorene.

cond-mat.mes-hall

Handover-Count based Velocity Estimation of Cellular-Connected UAVs

Cellular-connected unmanned aerial vehicles (UAVs) are expected to play a major role in various civilian and commercial applications in the future. While existing cellular networks can provide wireless coverage to UAV user equipment (UE), such legacy networks are optimized for ground users which makes it challenging to provide reliable connectivity to aerial UEs. To ensure reliable and effective mobility management for aerial UEs, estimating the velocity of cellular-connected UAVs carries critical importance. In this paper, we introduce an approximate probability mass function (PMF) of handover count (HOC) for different UAV velocities and different ground base station (GBS) densities. Afterward, we derive the Cramer-Rao lower bound (CRLB) for the velocity estimate of a UAV, and also provide a simple unbiased estimator for the UAV's velocity which depends on the GBS density and HOC measurement time. Our simulation results show that the accuracy of velocity estimation increases with the GBS density and HOC measurement window. Moreover, the velocity of commercially available UAVs can be estimated efficiently with reasonable accuracy.

eess.SP

RSS-Based Detection of Drones in the Presence of RF Interferers

Drones will have extensive use cases across various commercial, government, and military sectors, ranging from delivery of consumer goods to search and rescue operations. To maintain the safety and security of people and infrastructure, it becomes critically important to quickly and accurately detect non-cooperating drones. In this paper we formulate a received signal strength (RSS) based detector, leveraging the existing wireless infrastructures that might already be serving other devices. Thus the detector can detect the presence of a drone signal buried in radio frequency (RF) interference and thermal noise, in a mixed line-of-sight (LOS) and non-LOS (NLOS) environment. We develop analytical expressions for the probability of false alarm and the probability of detection of a drone, which quantify the impact of aggregate interference and air-to-ground (A2G) propagation characteristics on the detection performance of individual sensors. We also provide analytical expressions for the average network probability of detection, which capture the impact of sensor density on a network's detection coverage. Finally, we find the critical sensor density that maximizes the average network probability of detection for a given requirement of the probability of false alarm.

eess.SP

Analytic and numeric computation of edge states and conductivity of a Kane-Mele nanoribbon

We compute analytic expressions for the edge states in a zigzag Kane-Mele nanoribbon (KMNR) by solving the eigenvalue equations in presence of intrinsic and Rashba spin-orbit couplings. Owing to the P-T symmetry of the Hamiltonian the edge states are protected by topological invariance and hence are found to be robust. We have done a systematic study for each of the above cases, for example, a pristine graphene, graphene with an intrinsic spin-orbit coupling, graphene with a Rashba spin-orbit coupling, a Kane-Mele nanoribbon and supported our results on the robustness of the edge states by analytic computation of the electronic probability amplitudes, the local density of states (LDOS), band structures and the conductance spectra.

cond-mat.mes-hall