100 research outputs found

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    Annual Report 1984-1985

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    It contains the statement of R&D works undertaken, achivement made and the expenditure by the laboratory during the financial year 1984-1985

    Revolutionizing Future Connectivity: A Contemporary Survey on AI-empowered Satellite-based Non-Terrestrial Networks in 6G

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    Non-Terrestrial Networks (NTN) are expected to be a critical component of 6th Generation (6G) networks, providing ubiquitous, continuous, and scalable services. Satellites emerge as the primary enabler for NTN, leveraging their extensive coverage, stable orbits, scalability, and adherence to international regulations. However, satellite-based NTN presents unique challenges, including long propagation delay, high Doppler shift, frequent handovers, spectrum sharing complexities, and intricate beam and resource allocation, among others. The integration of NTNs into existing terrestrial networks in 6G introduces a range of novel challenges, including task offloading, network routing, network slicing, and many more. To tackle all these obstacles, this paper proposes Artificial Intelligence (AI) as a promising solution, harnessing its ability to capture intricate correlations among diverse network parameters. We begin by providing a comprehensive background on NTN and AI, highlighting the potential of AI techniques in addressing various NTN challenges. Next, we present an overview of existing works, emphasizing AI as an enabling tool for satellite-based NTN, and explore potential research directions. Furthermore, we discuss ongoing research efforts that aim to enable AI in satellite-based NTN through software-defined implementations, while also discussing the associated challenges. Finally, we conclude by providing insights and recommendations for enabling AI-driven satellite-based NTN in future 6G networks.Comment: 40 pages, 19 Figure, 10 Tables, Surve

    Ensemble Machine Learning for Individual Stock Investment

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    NASA Tech Briefs Index, 1976

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    Abstracts of new technology derived from the research and development activities of the National Aeronautics and Space Administration are presented. Emphasis is placed on information considered likely to be transferrable across industrial, regional, or disciplinary lines. Subject matter covered includes: electronic components and circuits; electronic systems; physical sciences; materials; life sciences; mechanics; machinery; fabrication technology; and mathematics and information sciences

    A SEASAT report. Volume 1: Program summary

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    The program background and experiment objectives are summarized, and a description of the organization and interfaces of the project are provided. The mission plan and history are also included as well as user activities and a brief description of the data system. A financial and manpower summary and preliminary results of the mission are also included

    Cumulative effects modeling in the mountaintop removal mining region of the central Appalachians

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    Anthropogenic alteration of natural land cover is a global driver of aquatic resource impairment. It is increasingly recognized that aquatic systems are impacted by multiple land use activities that combine additively and interactively to result in unique patterns of degradation (i.e., cumulative effects). Moreover, stream networks are multi-scaled, hierarchically structured systems wherein localized impacts can have both local (e.g., stream segment) and regional (e.g., watershed) consequences. Thus, there has been a recent push to construct statistical models capable of predicting and forecasting aquatic conditions under current and future landuse scenarios (i.e., scenario analysis) and characterize local and regional processes dictating observed patterns of ecological degradation.;Nowhere is there a greater need for decisive and empirically-driven aquatic resource management than within the Mountaintop Removal-Valley Fill (MTR-VF) mining region of the central Appalachians, where dramatic changes in land cover associated with large scale surface mining can produce strong measurable impacts to downstream ecosystems. However, several knowledge gaps currently limit aquatic resource management within this actively developing and socioeconomically important region. Notably, the extent to which surface mining-related stressors interact with those of other landuse activities is unclear.;In my first chapter, I tested for additive and interactive effects of dominant landuse activities (i.e., surface mining, deep mining, and residential development) on water quality (specific conductance and Se), habitat quality, and benthic macroinvertebrates via a uniquely designed watershed-scale assessment of the Coal River, West Virginia. I derived equations for predicting in-stream response to landscape changes and predicted the outcome of a realistic future scenario involving development of 15 permitted mines. I found that surface mining, underground mining, and residential development altered physical, chemical and biological condition through additive and complex interactive effects.;My second chapter focused on constructing landscape-based cumulative effects models capable of predicting in-stream response to future surface-mine development within the context of other landuse activities throughout the MTR-VF region. Predictive models provided precise estimates of specific conductance (model R2 ≤0.77 and cross-validated R2 ≤0.74), Se (0.74 and 0.70), and benthic macroinvertebrate community composition (0.72 and 0.65) and predicted high levels of chemical (33%) and biological (67%) impairment as a result of additive and interactive effects of surface mining, underground mining, and residential development. Of this total impairment, however, \u3c25% could be attributed to surface mining alone. Furthermore, the surface-mining level that results in exceedance of the 300 muS/cm conductivity benchmark increased from 4.4% in the presence of other stressors to 16.6% when only surface mining was present.;My third chapter focused on characterizing how multiple landuse activities control detailed patterns in local water chemistry. Principal component (PC) analysis identified 3 important dimensions of variation in water chemistry that were significantly correlated with contemporary surface mining (PC1, elevated dominant ions, sulfate, alkalinity, and selenium), coal geology and legacy mines (PC2, elevated trace metals), and residential development (PC3, elevated sodium and chloride). The combination of these 3 dominant sources of pollutants produced a complex stream-to-stream patchwork of contaminant mixtures. Seventy-five percent of headwater streams (catchments \u3c5km 2) had water chemistries that classified as either reference (49%), development only (18%) or mining only (8%). Only 21% of larger streams (catchments \u3e5km2) were classified as having reference chemistries, and chemistries indicative of combined mining and development contaminants accounted for 47% of larger streams (compared to 26% of headwater streams).;My fourth chapter was focused on quantifying the extent to which pervasive physicochemical degradation throughout the MTR-VF region influences regional metacommunity structure and processes. Notably, conservation of undisturbed headwater streams is a common management activity in disturbed watersheds because of their ability to preserve regional biodiversity. However, undisturbed headwater streams are often isolated within heavily degraded regions, leaving their communities at risk of losing sensitive, poor dispersing taxa (through decreased mass and rescue effects) and gaining tolerant, widely dispersing taxa (through increased dispersal and mass effects) from nearby degraded habitats. Results of this chapter suggest that both local (observed physicochemical conditions) and neighborhood (condition of streams within a 5km buffer) conditions explain significant variation in assemblage structure across all taxa. However, the strength of neighborhood effects varied as a function of taxon-specific tolerance and dispersal characteristics. Several taxa (Chironomidae, Hemerodromia, Chimarra) increased in occurrence and abundance with decreasing neighborhood conditions. Thus, invertebrate communities within even the most pristine streams are at risk when isolated within heavily impacted neighborhoods. Consequently, protection of regional species\u27 pools in heavily impacted regions will require more than simply conserving headwater catchments. (Abstract shortened by UMI.)

    FPGA implementations for parallel multidimensional filtering algorithms

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    PhD ThesisOne and multi dimensional raw data collections introduce noise and artifacts, which need to be recovered from degradations by an automated filtering system before, further machine analysis. The need for automating wide-ranged filtering applications necessitates the design of generic filtering architectures, together with the development of multidimensional and extensive convolution operators. Consequently, the aim of this thesis is to investigate the problem of automated construction of a generic parallel filtering system. Serving this goal, performance-efficient FPGA implementation architectures are developed to realize parallel one/multi-dimensional filtering algorithms. The proposed generic architectures provide a mechanism for fast FPGA prototyping of high performance computations to obtain efficiently implemented performance indices of area, speed, dynamic power, throughput and computation rates, as a complete package. These parallel filtering algorithms and their automated generic architectures tackle the major bottlenecks and limitations of existing multiprocessor systems in wordlength, input data segmentation, boundary conditions as well as inter-processor communications, in order to support high data throughput real-time applications of low-power architectures using a Xilinx Virtex-6 FPGA board. For one-dimensional raw signal filtering case, mathematical model and architectural development of the generalized parallel 1-D filtering algorithms are presented using the 1-D block filtering method. Five generic architectures are implemented on a Virtex-6 ML605 board, evaluated and compared. A complete set of results on area, speed, power, throughput and computation rates are obtained and discussed as performance indices for the 1-D convolution architectures. A successful application of parallel 1-D cross-correlation is demonstrated. For two dimensional greyscale/colour image processing cases, new parallel 2-D/3-D filtering algorithms are presented and mathematically modelled using input decimation and output image reconstruction by interpolation. Ten generic architectures are implemented on the Virtex-6 ML605 board, evaluated and compared. Key results on area, speed, power, throughput and computation rate are obtained and discussed as performance indices for the 2-D convolution architectures. 2-D image reconfigurable processors are developed and implemented using single, dual and quad MAC FIR units. 3-D Colour image processors are devised to act as 3-D colour filtering engines. A 2-D cross-correlator parallel engine is successfully developed as a parallel 2-D matched filtering algorithm for locating any MRI slice within a MRI data stack library. Twelve 3-D MRI filtering operators are plugged in and adapted to be suitable for biomedical imaging, including 3-D edge operators and 3-D noise smoothing operators. Since three dimensional greyscale/colour volumetric image applications are computationally intensive, a new parallel 3-D/4-D filtering algorithm is presented and mathematically modelled using volumetric data image segmentation by decimation and output reconstruction by interpolation, after simultaneously and independently performing 3-D filtering. Eight generic architectures are developed and implemented on the Virtex-6 board, including 3-D spatial and FFT convolution architectures. Fourteen 3-D MRI filtering operators are plugged and adapted for this particular biomedical imaging application, including 3-D edge operators and 3-D noise smoothing operators. Three successful applications are presented in 4-D colour MRI (fMRI) filtering processors, k-space MRI volume data filter and 3-D cross-correlator.IRAQI Government

    An integrated study of earth resources in the state of California using remote sensing techniques

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    The author has identified the following significant results. The effects on estimates of monthly volume runoff were determined separately for each of the following parameters: precipitation, evapotranspiration, lower zone and upper zone tension water capacity, imperviousness of the watershed, and percent of the watershed occupied by riparian vegetation, streams, and lakes. The most sensitive and critical parameters were found to be precipitation during the entire year and springtime evapotranspiration
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