1,721,426 research outputs found
RCal: A Case Study on Semantic Web Agents
No full textThe Semantic Web promises to change the way agents navigate, harvest and utilize information on the internet. By providing a structured, distributed representation for expressing concepts and relationships defined by multiple ontologies, it is now possible for agents to read and reason about published knowledge, without the need for scrapers, information agents, and centralized ontologies. We present the RETSINA Calendar Agent, a distributed meeting scheduler, that reads schedules (such as conference programs, events, etc) marked up in RDF on the Semantic Web, and imports these into the user’s Personal Information Manager. The embedded Semantic Web Browsing tool allows the user to explore related concepts within the schedule, and to query other agents and service providers for more information
Bayesian learning aided sparse channel estimation for orthogonal time frequency space modulated systems
No full textA novel sparse channel state information (CSI) estimation scheme is proposed for orthogonal time frequency space (OTFS) modulated systems, in which the pilots are directly transmitted over the time-frequency (TF)-domain grid for estimating the delay-Doppler (DD)-domain CSI. The proposed CSI estimation model leads to a reduction in the pilot overhead as well as the training duration required. Furthermore, it does not require a DD-domain guard interval between the pilot and data symbols, hence increasing the bandwidth efficiency. A novel Bayesian learning (BL) framework is proposed for CSI acquisition, which exploits the DD-domain sparsity for improving the estimation accuracy in comparison to the conventional minimum mean squared error (MMSE)-based scheme. A low complexity linear MMSE detector is used in the subsequent data detection phase. Our simulation results demonstrate the performance improvement of the proposed BL-based scheme over the conventional MMSE-based scheme as well as over other existing sparse estimation schemes
Bayesian learning aided simultaneous row and group sparse channel estimation in orthogonal time frequency space modulated MIMO systems
No full textA sparse channel state information (CSI) estimation model is proposed for reducing the pilot overhead of orthogonal time frequency space (OTFS) modulation aided multipleinput multiple-output (MIMO) systems. Explicitly, the pilots are directly transmitted over the time-frequency (TF)-domain grid for estimating the delay-Doppler (DD)-domain CSI that leads to a reduction of the pilot overhead, training duration and pre-processing complexity. Furthermore, it completely avoids placing multiple DD-domain guard intervals corresponding to each transmit antenna within the same OTFS frame, while keeping the training duration flexible, hence increasing the bandwidth efficiency. A unique benefit of the proposed CSI estimation model is that it can efficiently handle fractional Dopplers also. The resultant DD-domain CSI becomes simultaneously row and group (RG)-sparse. To exploit this compelling property, an orthogonal matching pursuit (OMP)-based RGOMP technique is developed, conveniently complemented by an enhanced Bayesian learning (BL)-based RG-BL framework, both of which substantially outperform the state-of-the-art methods. Furthermore, low-complexity linear detectors are designed for the ensuing data detection phase, which directly employ the estimated DD-domain sparse CSI, without assuming any further knowledge concerning the number of dominant multipath components. Finally, simulation results are provided to demonstrate performance improvement of the proposed BL-based schemes over the OMP and the state-of-the-art schemes
Delay-doppler and angular domain 4D-sparse CSI estimation in OTFS aided MIMO systems
No full textA convenient delay, Doppler and angular-(DDA) domain representation of the multiple-input multiple-output (MIMO) wireless channel is conceived for deriving the end to end relationship in the delay-Doppler (DD)-domain for orthogonal time frequency space (OTFS)-based communications. Subsequently, a time-domain pilot based model is developed for estimating the DDA-domain channel state information (CSI) of our MIMO OTFS system. The key differentiating feature of the CSI estimation model derived is its ability to exploit the 4-dimensional (4D)-sparsity arising in the DDA-domain, given the limited number of dominant scatterers. Furthermore, the training overhead of the proposed framework is low, and the pilot placement is quite flexible, necessitating no guard-interval. Finally, an orthogonal matching pursuit (OMP) framework is employed for 4D-sparse CSI acquisition, followed by deriving the Oracle minimum mean squared error (Oracle-MMSE) and its Bayesian Cramer-Rao lower bound (BCRLB). Our simulation results confirm the improved CSI estimation performance attained over the benchmarks
Browsing Schedules - An Agent-based approach to navigating the Semantic Web.
Get PDFThe Semantic Web promises to change the way agents navigate, harvest and utilize information on the internet. By providing a structured, distributed representation for expressing concepts and relationships defined by multiple ontologies, it is now possible for agents to read and reason about published knowledge, without the need for scrapers, information agents, and centralized ontologies. Agents can utilize this knowledge to seek and invoke other agents and web services, thus supporting navigation across the Semantic Web. We demonstrate how agents support enhanced navigation on the Semantic Web within a conference-schedule domain, and present three agent-based services: the RETSINA Calendar Agent, which reasons about schedules marked up on the Semantic Web; the DMA2ICal markup translation agent which provides translation services between schedules grounded in different ontologies, and a Conference Agent, that invokes the Calendar Agent
Extending Kolmogorov theory to polymeric turbulence
Get PDFWe present a formalism that reconciles polymeric turbulence with the classical Kolmogorov phenomenology. By relying on an appropriate form of the Kármán-Howarth-Monin-Hill equation, we define extended velocity increments and structure functions that also incorporate the non-Newtonian, polymeric contribution. The pth-order extended structure functions exhibit a power-law behavior in the elastoinertial range of scales, with exponents deviating from the analytically predicted value of p/3. These deviations are readily accounted for by considering local averages of the total dissipation rather than global averages. We also demonstrate the scale invariance of multiplier statistics of the extended velocity increments, whose distributions collapse for a wide range of scales
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Effect of heterostructure engineering on electronic structure and transport properties of two-dimensional halide perovskites
Get PDFOrganic-inorganic halide perovskite solar cells have attracted much attention due to their low-cost fabrication, flexibility, and high-power conversion efficiency. More recent efforts show that the reduction from three- to two-dimensions (2D) of organic–inorganic halide perovskites promises an exciting opportunity to tune their electronic properties. Here, we explore the effect of reduced dimensionality and heterostructure engineering on the intrinsic material properties, such as energy stability, bandgap and transport properties of 2D hybrid organic–inorganic halide perovskites using first-principles density functional theory. We show that the energy stability of engineered perovskite heterostructures is significantly enhanced. The heterostructures with improved stability also show excellent transport properties similar to their bulk counterparts. These layered chemistries demonstrate the advantage of a broad range of tunable bandgaps and high-absorption coefficient in the visible spectrum. The proposed 2D heterostructured material holds potential for nano-optoelectronic devices as well as for effective photovoltaics.This is a manuscript of an article published as Singh, Rahul, Prashant Singh, and Ganesh Balasubramanian. "Effect of heterostructure engineering on electronic structure and transport properties of two-dimensional halide perovskites." Computational Materials Science 200 (2021): 110823.
DOI: 10.1016/j.commatsci.2021.110823.
Copyright 2021 Elsevier B.V.
DOE Contract Number(s): AC02-07CH11358; CMMI-1753770.
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