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Academic literature on the topic 'SWAAMI'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "SWAAMI"

Gogoi, Mukunda Madhab, Venugopalan Nair Jayachandran, Aditya Vaishya, Surendran Nair Suresh Babu, Sreedharan Krishnakumari Satheesh, and Krishnaswamy Krishna Moorthy. "Airborne in situ measurements of aerosol size distributions and black carbon across the Indo-Gangetic Plain during SWAAMI–RAWEX." Atmospheric Chemistry and Physics 20, no. 14 (July 22, 2020): 8593–610. http://dx.doi.org/10.5194/acp-20-8593-2020.

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Abstract. During the combined South-West Asian Aerosol–Monsoon Interactions and Regional Aerosol Warming Experiment (SWAAMI–RAWEX), collocated airborne measurements of aerosol number–size distributions in the size (diameter) regime 0.5 to 20 µm and black carbon (BC) mass concentrations were made across the Indo-Gangetic Plain (IGP), for the first time, from three distinct locations, just prior to the onset of the Indian summer monsoon. These measurements provided an east–west transect of region-specific properties of aerosols as the environment transformed from mostly arid conditions of the western IGP (represented by Jodhpur, JDR) having dominance of natural aerosols to the central IGP (represented by Varanasi, VNS) having very high anthropogenic emissions, to the eastern IGP (represented by the coastal station Bhubaneswar, BBR) characterized by a mixture of the IGP outflow and marine aerosols. Despite these, the aerosol size distribution revealed an increase in coarse mode concentration and coarse mode mass fraction (fractional contribution to the total aerosol mass) with the increase in altitude across the entire IGP, especially above the well-mixed region. Consequently, both the mode radii and geometric mean radii of the size distributions showed an increase with altitude. However, near the surface and within the atmospheric boundary layer (ABL), the features were specific to the different subregions, with the highest coarse mode mass fraction (FMC∼72 %) in the western IGP and highest accumulation fraction in the central IGP with the eastern IGP in between. The elevated coarse mode fraction is attributed to mineral dust load arising from local production as well as due to advection from the west. This was further corroborated by data from the Cloud-Aerosol Transport System (CATS) on board the International Space Station (ISS), which also revealed that the vertical extent of dust aerosols reached as high as 5 km during this period. Mass concentrations of BC were moderate (∼1 µg m−3) with very little altitude variation up to 3.5 km, except over VNS where very high concentrations were seen near the surface and within the ABL. The BC-induced atmospheric heating rate was highest near the surface at VNS (∼0.81 K d−1), while showing an increasing pattern with altitude at BBR (∼0.35 K d−1 at the ceiling altitude).

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Vaishya, Aditya, Surendran Nair Suresh Babu, Venugopalan Jayachandran, Mukunda M. Gogoi, Naduparambil Bharathan Lakshmi, Krishnaswamy Krishna Moorthy, and Sreedharan Krishnakumari Satheesh. "Large contrast in the vertical distribution of aerosol optical properties and radiative effects across the Indo-Gangetic Plain during the SWAAMI–RAWEX campaign." Atmospheric Chemistry and Physics 18, no. 23 (December 13, 2018): 17669–85. http://dx.doi.org/10.5194/acp-18-17669-2018.

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Abstract. Measurements of the vertical profiles of the optical properties (namely the extinction coefficient and scattering and absorption coefficients respectively σext ∕ σscat ∕ σabs) of aerosols have been made across the Indo-Gangetic Plain (IGP) using an instrumented aircraft operated from three base stations – Jodhpur (JDR), representing the semi-arid western IGP; Varanasi (VNS), the central IGP characterized by significant anthropogenic activities; and the industrialized coastal location in the eastern end of the IGP (Bhubaneswar, BBR) – just prior to the onset of the Indian summer monsoon. The vertical profiles depicted region-specific absorption characteristics, while the scattering characteristics remained fairly uniform across the region, leading to a west–east gradient in the vertical structure of single-scattering albedo (SSA). Integrated from near the ground to 3 km, the highest absorption coefficient and hence the lowest SSA occurred in the central IGP (Varanasi). Size distribution, inferred from the spectral variation of the scattering coefficient, showed a gradual shift from coarse-particle dominance in the western IGP to strong accumulation dominance in the eastern coast with the central IGP coming in between, arising from a change in the aerosol type from a predominantly natural (dust and sea salt) type in the western IGP to a highly anthropogenic type (industrial emissions, fossil fuel and biomass combustion) in the eastern IGP, with the central IGP exhibiting a mixture of both. Aerosol-induced short-wave radiative forcing, estimated using altitude-resolved SSA information, revealed significant atmospheric warming in the central IGP, while a top-of-atmosphere cooling is seen, in general, in the IGP. Atmospheric heating rate profiles, estimated using altitude-resolved SSA and column-averaged SSA, revealed considerable underestimation in the latter case, emphasizing the importance and necessity of having altitude-resolved SSA information as against a single value for the entire column.

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Manoj, Mohanan R., Sreedharan K. Satheesh, Krishnaswamy K. Moorthy, Jamie Trembath, and Hugh Coe. "Measurement report: Altitudinal variation of cloud condensation nuclei activation across the Indo-Gangetic Plain prior to monsoon onset and during peak monsoon periods: results from the SWAAMI field campaign." Atmospheric Chemistry and Physics 21, no. 11 (June 14, 2021): 8979–97. http://dx.doi.org/10.5194/acp-21-8979-2021.

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Abstract. Vertical distributions (altitude profiles) of condensation nuclei (CN) and cloud condensation nuclei (CCN) and their spatial variations across the Indo-Gangetic Plain (IGP) have been investigated based on airborne measurements carried out during the SWAAMI field campaign (June to July 2016) capturing the contrasting phases of the Indian monsoon activity in 2016 just prior to its onset and during its active phase. Prior to the monsoon onset, high concentrations of CN and CCN prevailed across the IGP, and the profiles revealed frequent occurrence of elevated layers (in the altitude range 1–3 km). Highest concentrations and elevated peaks with high values occurred over the central IGP. The scenario changed dramatically during the active phase of the monsoon, when the CN and CCN concentrations dropped (CN by 20 % to 30 % and CCN by 6 % to 25 %) throughout the IGP with more pronounced changes at altitudes higher than 3 km where decreases as high as > 80 % were observed. These reductions have an east-to-west decreasing gradient, being most remarkable in the eastern IGP and very weak over the western IGP where the CN concentrations above 3 km increased during the monsoon. The activation ratios (ARs) showed contrasting features, increasing with increase in altitude, prior to the onset of monsoon, reversing the trend to decrease with increase in altitude during the active phase of the monsoon. The supersaturation spectrum became flatter during the active phase of the monsoon, indicating an increase in the hygroscopicity of aerosols following the mixing of surface-based emissions with the advected marine air mass.

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Pathak, Harshavardhana Sunil, Sreedharan Krishnakumari Satheesh, Ravi Shankar Nanjundiah, Krishnaswamy Krishna Moorthy, Sivaramakrishnan Lakshmivarahan, and Surendran Nair Suresh Babu. "Assessment of regional aerosol radiative effects under the SWAAMI campaign – Part 1: Quality-enhanced estimation of columnar aerosol extinction and absorption over the Indian subcontinent." Atmospheric Chemistry and Physics 19, no. 18 (September 24, 2019): 11865–86. http://dx.doi.org/10.5194/acp-19-11865-2019.

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Abstract. Improving the accuracy of regional aerosol climate impact assessment calls for improvement in the accuracy of regional aerosol radiative effect (ARE) estimation. One of the most important means of achieving this is to use spatially homogeneous and temporally continuous datasets of critical aerosol properties, such as spectral aerosol optical depth (AOD) and single scattering albedo (SSA), which are the most important parameters for estimating aerosol radiative effects. However, observations do not provide the above; the space-borne observations though provide wide spatial coverage, are temporal snapshots and suffer from possible sensor degradation over extended periods. On the other hand, the ground-based measurements provide more accurate and temporally continuous data but are spatially near-point observations. Realizing the need for spatially homogeneous and temporally continuous datasets on one hand and the near non-existence of such data over the south Asian region (which is one of the regions where aerosols show large heterogeneity in most of their properties), construction of accurate gridded aerosol products by synthesizing the long-term space-borne and ground-based data has been taken up as an important objective of the South West Asian Aerosol Monsoon Interactions (SWAAMI), a joint Indo-UK field campaign, aiming at characterizing aerosol–monsoon links and their variabilities over the Indian region. In Part 1 of this two-part paper, we present spatially homogeneous gridded datasets of AOD and absorption aerosol optical depth (AAOD), generated for the first time over this region. These data products are developed by merging the highly accurate aerosol measurements from the dense networks of 44 (for AOD) and 34 (for AAOD) ground-based observatories of Aerosol Radiative Forcing over India NETwork (ARFINET) and AErosol RObotic NETwork (AERONET) spread across the Indian region, with satellite-retrieved AOD and AAOD, following statistical assimilation schemes. The satellite data used for AOD assimilation include AODs retrieved from MODerate Imaging Spectroradiometer (MODIS) and Multiangle Imaging SpectroRadiometer (MISR) over the same domain. For AAOD, the ground-based black carbon (BC) mass concentration measurements from the network of 34 ARFINET observatories and satellite-based (Kalpana-1, INSAT-3A) infrared (IR) radiance measurements are blended with gridded AAODs (500 nm, monthly mean) derived from Ozone Monitoring Instrument (OMI)-retrieved AAODs (at 354 and 388 nm). The details of the assimilation methods and the gridded datasets generated are presented in this paper. The merged gridded AOD and AAOD products thus generated are validated against the data from independent ground-based observatories, which were not used for the assimilation process but are representative of different subregions of the complex domain. This validation exercise revealed that the independent ground-based measurements are better confirmed by merged datasets than the respective satellite products. As ensured by assimilation techniques employed, the uncertainties in merged AODs and AAODs are significantly less than those in corresponding satellite products. These merged products also all exhibit important large-scale spatial and temporal features which are already reported for this region. Nonetheless, the merged AODs and AAODs are significantly different in magnitude from the respective satellite products. On the background of above-mentioned quality enhancements demonstrated by merged products, we have employed them for deriving the columnar SSA and analysed its spatiotemporal characteristics. The columnar SSA thus derived has demonstrated distinct seasonal variation over various representative subregions of the study domain. The uncertainties in the derived SSA are observed to be substantially less than those in OMI SSA. On the backdrop of these benefits, the merged datasets are employed for the estimation of regional aerosol radiative effects (direct), the results of which would be presented in a companion paper, Part 2 of this two-part paper.

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Manoj, Mohanan R., Sreedharan K. Satheesh, Krishnaswamy K. Moorthy, and Hugh Coe. "Vertical profiles of submicron aerosol single scattering albedo over the Indian region immediately before monsoon onset and during its development: research from the SWAAMI field campaign." Atmospheric Chemistry and Physics 20, no. 6 (April 2, 2020): 4031–46. http://dx.doi.org/10.5194/acp-20-4031-2020.

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Abstract. Vertical structures of aerosol single scattering albedo (SSA), from near the surface through the free troposphere, have been estimated for the first time at distinct geographical locations over the Indian mainland and adjoining oceans, using in situ measurements of aerosol scattering and absorption coefficients aboard the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft during the South West Asian Aerosol Monsoon Interactions (SWAAMI) campaign from June to July 2016. These are used to examine the spatial variation of SSA profiles and also to characterize its transformation from just prior to the onset of Indian Summer Monsoon (June 2016) to its active phase (July 2016). Very strong aerosol absorption, with SSA values as low as 0.7, persisted in the lower altitudes (<3 km) over the Indo-Gangetic Plains (IGP), prior to the monsoon onset, with a west-to-east gradient; lower values occurred in the north-western arid regions, peaking in the central IGP and somewhat decreasing towards the eastern end. During the active phase of the monsoon, the SSA is found to increase remarkably, indicating far less absorption. Nevertheless, significant aerosol absorption persisted in the lower and middle troposphere over the IGP. Inputting these SSA and extinction profiles into a radiative transfer model, we examined the effects of using height-resolved information in estimating atmospheric heating rates due to aerosols, over similar estimates made using a single columnar value. It was noted that use of a single SSA value leads to an underestimation (overestimation) of the heating rates over regions with low (high) SSA, emphasizing the importance of height-resolved information. Further, the use of realistic profiles showed significant heating of the atmosphere by submicron aerosol absorption at the middle troposphere, which may have strong implications for clouds and climate.

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Pathak, Harshavardhana Sunil, Sreedharan Krishnakumari Satheesh, Krishnaswamy Krishna Moorthy, and Ravi Shankar Nanjundiah. "Assessment of regional aerosol radiative effects under the SWAAMI campaign – Part 2: Clear-sky direct shortwave radiative forcing using multi-year assimilated data over the Indian subcontinent." Atmospheric Chemistry and Physics 20, no. 22 (November 23, 2020): 14237–52. http://dx.doi.org/10.5194/acp-20-14237-2020.

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Abstract. Clear-sky, direct shortwave aerosol radiative forcing (ARF) has been estimated over the Indian region, for the first time employing multi-year (2009–2013) gridded, assimilated aerosol products, as an important part of the South West Asian Aerosol Monsoon Interactions (SWAAMI) which is a joint Indo-UK research field campaign focused at understanding the variabilities in atmospheric aerosols and their interactions with the Indian summer monsoon. The aerosol datasets have been constructed following statistical assimilation of concurrent data from a dense network of ground-based observatories and multi-satellite products, as described in Part 1 of this two-part paper. The ARF, thus estimated, is assessed for its superiority or otherwise over other ARF estimates based on satellite-retrieved aerosol products, over the Indian region, by comparing the radiative fluxes (upward) at the top of the atmosphere (TOA) estimated using assimilated and satellite products with spatiotemporally matched radiative flux values provided by CERES (Clouds and Earth's Radiant Energy System) single-scan footprint (SSF) product. This clearly demonstrated improved accuracy of the forcing estimates using the assimilated vis-à-vis satellite-based aerosol datasets at regional, subregional and seasonal scales. The regional distribution of diurnally averaged ARF estimates has revealed (a) significant differences from similar estimates made using currently available satellite data, not only in terms of magnitude but also the sign of TOA forcing; (b) the largest magnitudes of surface cooling and atmospheric warming over the Indo-Gangetic Plain (IGP) and arid regions from north-western India; and (c) negative TOA forcing over most parts of the Indian region, except for three subregions – the IGP, north-western India and eastern parts of peninsular India where the TOA forcing changes to positive during pre-monsoon season. Aerosol-induced atmospheric warming rates, estimated using the assimilated data, demonstrate substantial spatial heterogeneities (∼0.2 to 2.0 K d−1) over the study domain with the IGP demonstrating relatively stronger atmospheric heating rates (∼0.6 to 2.0 K d−1). There exists a strong seasonality as well, with atmospheric warming being highest during pre-monsoon and lowest during winter seasons. It is to be noted that the present ARF estimates demonstrate substantially smaller uncertainties than their satellite counterparts, which is a natural consequence of reduced uncertainties in assimilated vis-à-vis satellite aerosol properties. The results demonstrate the potential application of the assimilated datasets and ARF estimates for improving accuracies of climate impact assessments at regional and subregional scales.

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Jayachandran, Venugopalan Nair, Surendran Nair Suresh Babu, Aditya Vaishya, Mukunda M. Gogoi, Vijayakumar S. Nair, Sreedharan Krishnakumari Satheesh, and Krishnaswamy Krishna Moorthy. "Altitude profiles of cloud condensation nuclei characteristics across the Indo-Gangetic Plain prior to the onset of the Indian summer monsoon." Atmospheric Chemistry and Physics 20, no. 1 (January 17, 2020): 561–76. http://dx.doi.org/10.5194/acp-20-561-2020.

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Abstract. Concurrent measurements of the altitude profiles of the concentration of cloud condensation nuclei (CCN), as a function of supersaturation (ranging from 0.2 % to 1.0 %), and aerosol optical properties (scattering and absorption coefficients) were carried out aboard an instrumented aircraft across the Indo-Gangetic Plain (IGP) just prior to the onset of the Indian summer monsoon (ISM) of 2016. The experiment was conducted under the aegis of the combined South-West Asian Aerosol–Monsoon Interactions and Regional Aerosol Warming Experiment (SWAAMI–RAWEX) campaign. The measurements covered coastal, urban and arid environments. In general, the CCN concentration was highest in the central IGP, decreasing spatially from east to west above the planetary boundary layer (PBL), which is ∼1.5 km for the IGP during pre-monsoon period. Despite this, the CCN activation efficiency at 0.4 % supersaturation was, interestingly, the highest over the eastern IGP (∼72 %), followed by that in the west (∼61 %), and it was the least over the central IGP (∼24 %) within the PBL. In general, higher activation efficiency is noticed above the PBL than below it. The central IGP showed remarkably low CCN activation efficiency at all altitudes, which appears to be associated with high black carbon (BC) mass concentration there, indicating the role of anthropogenic sources in suppressing the CCN efficiency. These first-ever CCN measurements over the western IGP, encompassing “the Great Indian Desert” also known as “the Thar Desert”, showed high CCN efficiency, ∼61 % at 0.4 % supersaturation, indicating the hygroscopic nature of the dust. The vertical structure of CCN properties is found to be air mass dependent, with higher activation efficiency even over the central IGP during the prevalence of marine air mass. Wet scavenging associated with precipitation episodes seems to have reduced the CCN activation efficiency below cloud level. An empirical relation has emerged between the CCN concentration and the scattering aerosol index (AI), which would facilitate the prediction of CCN from aerosol optical properties.

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Sangeetha, M. "Thiruvasaka Sivapurana - Comparison of Texts." Shanlax International Journal of Tamil Research 6, no. 4 (April 1, 2022): 104–13. http://dx.doi.org/10.34293/tamil.v6i4.4831.

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Panniruthirumuraigal of the Tamil Literature Series, which is revered as the chief textbook of the Vedic religion, are among the most easily explained texts on Saiva samayam in the community. The benefactors of the Panniruthirumuraigal are 27 benefactors. The first three of the twelve tirumuras were performed by Thirunana Samandar, the fourth, fifth and sixth tirumuras by Thirunavukkara, the seventh tirumura by Sundaramoorthy swamis, the eighth tirumura by nine arulas, the tenth tirumura by Tirumoolar and the eleventh tirumura by Sivan with twelve arulas. Twelfth tirumura by Sekizhar swami. Thiruvasakam is the eighth edition of the Panniruthirumuraigal. Many people have written texts for this book from time to time. This article examine variations in the the first part of Sivapuranam out of 51 parts in Thiruvasagam. The texts of the Thiruvasagam are numerous. In these discourses only the first part of the Sivapuranam of the three texts titled Thiruvasaka Urai Dharmapura Adinam’s Thiruvasaka Urai, written by Dantapani Desikar and published by Dantapani Desikar, compiled by the Srikali Thandavaraya Swamis and published by Thiruvaduthurai Adinam, is compared.The structure of this article is a comparison of texts of the Shiva Purana 1. General structure of Sivapurana, 2.System of Sivapurana texts, 3.Comparison of texts.

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Kilfoil, Mark, and Ali Ghorbani. "SWAMI." International Journal of Information Technology and Web Engineering 4, no. 3 (July 2009): 1–24. http://dx.doi.org/10.4018/jitwe.2009100601.

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The rapid growth of the World Wide Web has complicated the process of Web browsing by providing an overwhelming wealth of choices for the end user. To alleviate this burden, intelligent tools can do much of the drudge-work of looking ahead, searching and performing a preliminary evaluation of the end pages on the user’s behalf, anticipating the user’s needs and providing the user with more information with which to make fewer, more informed decisions. However, to accomplish this task, the tools need some form of representation of the interests of the user. This article describes the SWAMI system: SWAMI stands for Searching the Web with Agents having Mobility and Intelligence. SWAMI is a prototype that uses a multi-agent system to represent the interests of a user dynamically, and take advantage of the active nature of agents to provide a platform for look-ahead evaluation, page searching, and link swapping. The collection of agents is organized hierarchically according to the apparent interests of the user, which are discovered on-the-fly through multistage clustering. Results from initial testing show that such a system is able to follow the multiple changing interests of a user accurately, and that it is capable of acting fruitfully on these interests to provide a user with useful navigational suggestions.

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Hendricks, Eric A., Jonathan L. Vigh, and Christopher M. Rozoff. "Forced, Balanced, Axisymmetric Shallow Water Model for Understanding Short-Term Tropical Cyclone Intensity and Wind Structure Changes." Atmosphere 12, no. 10 (October 7, 2021): 1308. http://dx.doi.org/10.3390/atmos12101308.

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A minimal modeling system for understanding tropical cyclone intensity and wind structure changes is introduced: Shallow Water Axisymmetric Model for Intensity (SWAMI). The forced, balanced, axisymmetric shallow water equations are reduced to a canonical potential vorticity (PV) production and inversion problem, whereby PV is produced through a mass sink (related to the diabatic heating) and inverted through a PV/absolute–angular–momentum invertibility principle. Because the invertibility principle is nonlinear, a Newton–Krylov method is used to iteratively obtain a numerical solution to the discrete problem. Two versions of the model are described: a physical radius version which neglects radial PV advection (SWAMI-r) and a potential radius version that naturally includes the advection in the quasi-Lagrangian coordinate (SWAMI-R). In idealized numerical simulations, SWAMI-R produces a thinner and more intense PV ring than SWAMI-r, demonstrating the role of axisymmetric radial PV advection in eyewall evolution. SWAMI-R always has lower intensification rates than SWAMI-r because the reduction in PV footprint effect dominates the peak magnitude increase effect. SWAMI-r is next demonstrated as a potentially useful short-term wind structure forecasting tool using the newly added FLIGHT+ Dataset azimuthal means for initialization and forcing on three example cases: a slowly intensifying event, a rapid intensification event, and a secondary wind maximum formation event. Then, SWAMI-r is evaluated using 63 intensifying cases. Even though the model is minimal, it is shown to have some skill in short-term intensity prediction, highlighting the known critical roles of the relationship between the radial structures of the vortex inertial stability and diabatic heating rate. Because of the simplicity of the models, SWAMI simulations are completed in seconds. Therefore, they may be of some use for hurricane nowcasting to short-term (less than 24 h) intensity and structure forecasting. Due to its favorable assumptions for tropical cyclone intensification, a potential use of SWAMI is a reasonable short-term upper-bound intensity forecast if the storm intensifies.

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Dissertations / Theses on the topic "SWAAMI"

McNabb, Andrew W. "Parallel Particle Swarm Optimization and Large Swarms." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2480.

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Optimization is the search for the maximum or minimum of a given objective function. Particle Swarm Optimization (PSO) is a simple and effective evolutionary algorithm, but it may take hours or days to optimize difficult objective functions which are deceptive or expensive. Deceptive functions may be highly multimodal and multidimensional, and PSO requires extensive exploration to avoid being trapped in local optima. Expensive functions, whose computational complexity may arise from dependence on detailed simulations or large datasets, take a long time to evaluate. For deceptive or expensive objective functions, PSO must be parallelized to use multiprocessor systems and clusters efficiently. This thesis investigates the implications of parallelizing PSO and in particular, the details of parallelization and the effects of large swarms. PSO can be expressed naturally in Google's MapReduce framework to develop a simple and robust parallel implementation that automatically includes communication, load balancing, and fault tolerance. This flexible implementation makes it easy to apply modifications to the algorithm, such as those that improve optimization of difficult objective functions and improve parallel performance. Results show that larger swarms help with both of these goals, but they are most effective if arranged into sparse topologies with lower overhead from communication. Additionally, PSO must be modified to use communication more efficiently in a large sparse swarm for objective functions where information ideally flows quickly through a large swarm. Swarm size is usually fixed at a modest number around 50, but particularly in a parallel computational environment, much larger swarms are much more effective for deceptive objective functions. Likewise, swarms much smaller than 50 are more effective for expensive but less deceptive functions. In general, swarm size should be carefully chosen using all available information about the objective function and computational environment.

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Riyaz, Firasath Maurer Peter M. Marks Robert J. "Evolving a Disjunctive Predator Prey Swarm using PSO Adapting Swarms with Swarms/." Waco, Tex. : Baylor University, 2005. http://hdl.handle.net/2104/1465.

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Ashcraft, C. Chace. "Moderating Influence as a Design Principle for Human-Swarm Interaction." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7406.

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Robot swarms have recently become of interest in both industry and academia for their potential to perform various difficult or dangerous tasks efficiently. As real robot swarms become more of a possibility, many desire swarms to be controlled or directed by a human, which raises questions regarding how that should be done. Part of the challenge of human-swarm interaction is the difficulty of understanding swarm state and how to drive the swarm to produce emergent behaviors. Human input could inhibit desirable swarm behaviors if their input is poor and has sufficient influence over swarm agents, affecting its overall performance. Thus, with too little influence, human input is useless, but with too much, it can be destructive. We suggest that there is some middle level, or interval, of human influence that allows the swarm to take advantage of useful human input while minimizing the effect of destructive input. Further, we propose that human-swarm interaction schemes can be designed to maintain an appropriate level of human influence over the swarm and maintain or improve swarm performance in the presence of both useful and destructive human input. We test this theory by implementing a piece of software to dynamically moderate influence and then testing it with a simulated honey bee colony performing nest site selection, simulated human input, and actual human input via a user study. The results suggest that moderating influence, as suggested, is important for maintaining high performance in the presence of both useful and destructive human input. However, while our software seems to successfully moderate influence with simulated human input, it fails to do so with actual human input.

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Nagavalli, Sasanka. "Algorithms for Timing and Sequencing Behaviors in Robotic Swarms." Research Showcase @ CMU, 2018. http://repository.cmu.edu/dissertations/1215.

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Robotic swarms are multi-robot systems whose global behavior emerges from local interactions between individual robots and spatially proximal neighboring robots. Each robot can be programmed with several local control laws that can be activated depending on an operator’s choice of global swarm behavior (e.g. flocking, aggregation, formation control, area coverage). In contrast to other multi-robot systems, robotic swarms are inherently scalable since they are robust to addition and removal of members with minimal system reconfiguration. This makes them ideal for applications such as search and rescue, environmental exploration and surveillance. Practical missions often require a combination of swarm behaviors and may have dynamically changing mission goals. However, a robotic swarm is a complex distributed dynamical system, so its state evolution depends on the timing as well as sequence of the supervisory inputs. Thus, it is difficult to predict the effects of an input on the state evolution of the swarm. More specifically, after becoming aware of a change in mission goals, it is unclear at what time a supervisory operator must convey this information to the swarm or which combination of behaviors to use to accomplish the new goals. The main challenges we address in this thesis are characterizing the effects of input timing on swarm performance and using this theory to inform automated composition of swarm behaviors to accomplish updated mission goals. We begin by formalizing the notion of Neglect Benevolence — the idea that delaying the application of an input can sometimes be beneficial to overall swarm performance — and using the developed theory to demonstrate experimentally that humans can learn to approximate optimal input timing. In an adversarial setting, we also demonstrate that by altering only the timing of consensus updates for a subset of the swarm, we can influence the agreement point of the entire swarm. Given a library of swarm behaviors, automated behavior composition consists of identifying a behavior schedule that must specify (1) the appropriate sequence of behaviors and (2) the corresponding duration of execution for each behavior. Applying our notion of Neglect Benevolence, it is clear these two parts are intricately interdependent. By first assuming the durations are known, we present an algorithm to identify the optimal behavior sequence to achieve a desired swarm mission goal when our library contains general swarm behaviors. By restricting our library to consensus-based swarm behaviors, we then relax the assumption on known durations and present an algorithm to simultaneously find the sequence and durations of swarm behaviors to time-optimally accomplish multiple unordered goals.

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Grosh, John Rolfes. "Multi-Human Management of a Hub-Based Colony: Efficiency and Robustness in the Cooperative Best M-of-N Task." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8544.

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Swarm robotics is an emerging field that is expected to provide robust solutions to spatially distributed problems. Human operators will often be required to guide a swarm in the fulfillment of a mission. Occasionally, large tasks may require multiple spatial swarms to cooperate in their completion. We hypothesize that when latency, bandwidth, operator dropout, and communication noise are significant factors, human organizations that promote individual initiative perform more effectively and resiliently than hierarchies in the cooperative best-m-of-n task. Simulations automating the behavior of hub-based swarm robotic agents and groups of human operators are used to evaluate this hypothesis. To make the comparisons between the team and hierarchies meaningful, we explore parameter values determining how simulated human operators behave in teams and hierarchies to optimize the performance of the respective organizations. We show that simulation results generally support the hypothesis with respect to the effect of latency and bandwidth on organizational performance.

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Grandi, Raffaele <1976&gt. "Coordination and Control of Autonomous Mobile Robots Swarms by using Particle Swarm Optimization Algorithm and Consensus Theory." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5904/1/Grandi_Raffaele_tesi.pdf.

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This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.

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Baumfield, Vivienne Marie. "Swami Vivekananda's practical Vedanta." Thesis, University of Newcastle upon Tyne, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261122.

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Gazi, Veysel. "Stability Analysis of Swarms." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1029812963.

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Swaim, Zachary Taylor. "Lipid metabolism by right whales using fecal samples to assess assimilation of copepod triacylglycerols and wax esters /." View electronic thesis, 2008. http://dl.uncw.edu/etd/2008-1/swaimz/zacharyswaim.pdf.

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Books on the topic "SWAAMI"

Chattopadhyay, Sharatchandra. Swami. Calcutta: Aditya, 1989.

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Swami. New York: Paragon House, 1990.

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Sharadbabu. Swami. Anand: Ravani Prakashan, 1988.

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Boyd, Doug. Swami. Honesdale, Pa: Himalayan International Institute of Yoga Science and Philosophy of the U.S.A., 1995.

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Swami. Honesdale, Penn: Himalayan Institute Press, 2000.

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The laughing swamis: Australian sannyasin disciples of Swami Satyananda Saraswati and Osho Rajneesh. Delhi: Motilal Banarsidass Publishers, 1994.

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1932-, Jaidev Swami, and Ma Devi, eds. The laughing Swami: Teachings of Swami Hariharananda. Saint Paul, Minn: Yes International Publishers, 2005.

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Swami Vivekananda. New Delhi: Oxford University Press, 2000.

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Athavale, Bhe Va. Sagar swami. New Delhi: Vidya Vihar, 2002.

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S, Paul. Swami Vivekananda. New Delhi: Learners Press, 1998.

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Book chapters on the topic "SWAAMI"

Kordon, Arthur K. "Swarm Intelligence: The Benefits of Swarms." In Applying Computational Intelligence, 145–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-69913-2_6.

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Chen, Guochu, and Jinshou Yu. "Two Sub-swarms Particle Swarm Optimization Algorithm." In Lecture Notes in Computer Science, 515–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11539902_63.

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Kazadi, Sanza. "Using Swarm Engineering to Design Physicomimetic Swarms." In Physicomimetics, 529–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22804-9_17.

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Ramlakhan, Priyanka. "Swami Sivananda." In Hinduism and Tribal Religions, 1–6. Dordrecht: Springer Netherlands, 2018. http://dx.doi.org/10.1007/978-94-024-1036-5_629-1.

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Palit, Projit Kumar. "Swami Vivekananda." In Reappraising Modern Indian Thought, 73–100. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1415-7_4.

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Rinehart, Robin. "Swami Muktananda." In Hinduism and Tribal Religions, 1565–67. Dordrecht: Springer Netherlands, 2022. http://dx.doi.org/10.1007/978-94-024-1188-1_1414.

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Long, Jeffery D. "Swami Vivekananda." In Hinduism and Tribal Religions, 1574–81. Dordrecht: Springer Netherlands, 2022. http://dx.doi.org/10.1007/978-94-024-1188-1_1717.

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Ramlakhan, Priyanka. "Swami Sivananda." In Hinduism and Tribal Religions, 1569–74. Dordrecht: Springer Netherlands, 2022. http://dx.doi.org/10.1007/978-94-024-1188-1_629.

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Rinehart, Robin. "Swami Vivekananda." In The Routledge Handbook of Hindu–Christian Relations, 307–15. Abingdon, Oxon; New York: Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9781003139843-30.

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Xia, Lirong, Jizheng Chu, and Zhiqiang Geng. "A New Multi-Swarms Competitive Particle Swarm Optimization Algorithm." In Lecture Notes in Electrical Engineering, 133–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-26001-8_18.

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Conference papers on the topic "SWAAMI"

Kalivarapu, Vijay K., and Eliot H. Winer. "Parallel Implementation of Particle Swarm Optimization (PSO) Through Digital Pheromone Sharing." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49444.

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In this paper, a parallelization model for PSO through sharing of digital pheromones between multiple particle swarms to search n-dimensional design spaces is presented. Digital pheromones are models simulating real pheromones produced by insects for communication to indicate a source of food or a nesting location. Particle swarms search the design space with digital pheromones aiding communication within the swarm to improve search efficiency. Digital pheromones have demonstrated the capability of searching design spaces within PSO in the previous work by authors in both single and coarse granular parallel computing environments. Multiple swarms are simultaneously deployed across various processors in the coarse granular scheme and synchronization is carried out only when all swarms achieved convergence. This was done in an effort to reduce processor-to-processor communication and network latencies. With an appropriate parallelization scheme, the benefits of digital pheromones and swarm communication can potentially outweigh the network latencies resulting in improved search efficiency and accuracy. A swarm is deployed in the design space across different processors to explore this idea. Each part of the swarm is made to communicate with each other through an additional processor. Digital pheromones aiding within a swarm, communication between swarms is facilitated through the developed parallelization model. In this paper, the development and implementation of this method together with benchmarking test cases are presented.

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Morikawa, Koichi, Shigeyuki Urano, Toshiyuki Sanada, and Takayuki Saito. "Energy Spectral Properties Due to Bubble-Liquid Interaction in Oscillating-Grid Turbulence." In 16th International Conference on Nuclear Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/icone16-48470.

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In the present study, liquid-phase turbulence modulation induced by bubble swarms ascending in arbitrary turbulence is experimentally investigated. Liquid-phase homogeneous isotropic turbulence is formed using an oscillating grid in a cylindrical acrylic vessel of 149 mm in inner diameter. A bubble swarm of 19 bubbles is examined. The bubble size and generating time are completely controlled applying a bubble generating device using audio speakers. The bubble swarms are generated at a frequency of 4 Hz. The motion of individual bubbles of the bubble swarm is captured by a high-speed video camera. The liquid phase motion is also measured by PIV. The turbulence intensity, spatial correlation, integral scale and energy spectrum are calculated from the PIV data. It is confirmed that the oscillating-grid turbulence is an isotropic turbulence from the PIV result. When the bubble swarm is added, the original isotropic turbulence is modulated to an anisotropic turbulence by the mutual interaction between the bubble swarm and ambient isotropic turbulence. Moreover the bubble motion is notably changed. The bubble swarm contributes an increase of the energy spectrum to the ambient oscillating-grid turbulence. Moreover the suppression of energy spectrum occurred by interaction between bubble swarm and oscillating-grid turbulence compared with the energy spectrum in the flow induced by bubble swarms.

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Kumar, Ajitabh. "Joint Optimization of Well Placement and Control Using Multi-Stage, Multi-Swarm PSO." In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22045-ms.

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Abstract Evolutionary optimization algorithms, including particle swarm optimization (PSO), have been successfully applied in oil industry for production planning and control. Such optimization studies are quite challenging due to large number of decision variables, production scenarios, and subsurface uncertainties. In this work, multi-stage, multi-swarm PSO (MS2PSO) algorithm is proposed to fix certain issues with canonical PSO algorithm such as premature convergence, excessive influence of global best solution, and oscillation. Multiple experiments are conducted using Olympus benchmark to compare the efficacy of algorithms. Results from canonical PSO are first compared with two PSO variations in which hyperparameters are tuned to prioritize exploration in early phase and exploitation in late phase. Firstly, linearly decreasing inertia weight (LDIW-PSO) is used to have greater weight of current particle position during initial iterations, and vice versa. Then, time-varying acceleration coefficients (TVAC-PSO) are used to have greater weight of personal best and lesser weight of global best during the initial iterations, and vice versa. Next, a two-stage multi-swarm PSO (2SPSO) is used where multiple-swarms of the first stage collapse into a single swarm in the second stage. Finally, MS2PSO with multiple stages and multiple swarms is used in which swarms recursively collapse after each stage. Multiple swarm strategy ensures that diversity is retained within the population and multiple modes are explored. Staging ensures that local optima found during initial stage does not lead to premature convergence. Optimization test case comprises of 90 control variables of which 72 are well control related and 18 are well placement related. Swarm intelligence refers to global patterns emerging from simple interactions among population. Algorithmic rules at micro level lead to social interaction at meso level, which then further leads to collective behavior at macro level. It is observed that different algorithm designs have their own benefits and drawbacks. Decreasing inertia weight in LDIW-PSO enables exploration in early stages and convergence around global best in the later stages. TVAC-PSO on the other hand restricts social learning and aids exploration in the early iterations. Social learning component is increased as run progresses, and population moves towards global best. 2SPSO aids in exploring multi-modal objective space, thus preventing premature convergence to a local optima. Swarms collapse into one group in the second stage, and run finally converges towards global best. Multiple swarms and stages in MS2PSO ensure that diversity in population is maintained throughout the run which enables continuous learning, and thus mitigates premature convergence. Both 2SPSO and MS2PSO are found to be helpful for problems with high dimensions and multiple modes where greater degree of exploration is desired. Commercial cloud computing and parallel programming were used to handle high computational workload and reduce run-time from weeks to days. Coefficients of canonical PSO are tuned in LDIW-PSO and TVAC-PSO, which helps in mitigating issues like premature convergence and oscillation. Two-stage PSO (2SPSO) where multiple swarms of first stage collapse into one in second stage, and multi-stage multi-swarm PSO (MS2PSO) where swarms recursively collapse into one are proposed. These algorithms modify the social behavior at meso scale based on number of swarms, number of stages and iterations in each stage.

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Schumann, Hans, Louis Rosenberg, and Gregg Willcox. "'"Human Swarms” of novice sports fans beat professional handicappers when forecasting NFL football games." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003287.

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The biological phenomenon of Swarm Intelligence (SI) enables social species to converge on group decisions by interacting in real-time systems. Studied in schools of fish, bee swarms, and bird flocks, biologists have shown for decades that SI can greatly amplify group intelligence in natural systems. Artificial Swarm Intelligence (ASI) is a computer-mediated technique developed in 2015 to enable networked human groups to form real-time systems that can deliberate and converge on decisions, predictions, estimations, and prioritizations. A unique combination of real-time HCI methods and AI algorithms, ASI technology (also called “Human Swarming” or “Swarm AI”) has been shown in many studies to amplify group intelligence in forecasting tasks, often enabling small groups of non-professionals to exceed expert level performance. In the current study, small groups of approximately 24 amateur sports fans used an online platform called Swarm to collaboratively make weekly predictions (against the spread) of every football game in four consecutive NFL seasons (2019 - 2022) for a total of 1027 forecasted games. Approximately 5 games per week (as forecast by the human swarm) were identified as “predictable” using statistical heuristics. Performance was compared against the Vegas betting markets and measured against accepted performance benchmarks for professional handicappers. It is well known that professional bettors rarely achieve more than 55% accuracy against the Vegas spread and that top experts in the world rarely exceed 58% accuracy. In this study the amateur sports fans achieved 62.5% accuracy against the spread when connected as real-time “swarms.” A statistical analysis of this result (across 4 NFL seasons) found that swarms outperformed the 55% accuracy benchmark for human experts with significance (p=0.002). These results confirmed for the first time that groups of amateurs, when connected in real-time using ASI, can consistently generate forecasts that exceeded expert level performance with a high degree of statistical certainty.Keywords: Swarm Intelligence, Artificial Swarm Intelligence, Collective Intelligence, Wisdom of Crowds, Hyperswarms,

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Go¨z, Manfred F., Martin Sommerfeld, Bernard Bunner, and Gretar Tryggvason. "Microstructure of a Bidisperse Swarm of Spherical Bubbles." In ASME 2002 Joint U.S.-European Fluids Engineering Division Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/fedsm2002-31395.

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Three-dimensional simulations of bidisperse bubble swarms rising in a liquid have been carried out. This article describes the microstructure of a swarm of mostly spherical bubbles representing 6% void fraction. The swarm consists of an equal number of large and small bubbles with volume ratio 2. While the behavior of the large bubbles is similar to that in a comparable monodisperse system, the behavior of the small bubbles is different.

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Edwards, Victoria, Paulo Rezeck, Luiz Chaimowicz, and M. Ani Hsieh. "Segregation of Heterogeneous Robotics Swarms via Convex Optimization." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9653.

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The division of labor amongst a heterogeneous swarm of robots increases the range and sophistication of the tasks the swarm can accomplish. To efficiently execute a task the swarm of robots must have some starting organization. Over the past decade segregation of robotic swarms has grown as a field of research drawing inspiration from natural phenomena such as cellular segregation. A variety of different approaches have been undertaken to devise control methods to organize a heterogeneous swarm of robots. In this work, we present a convex optimization approach to segregate a heterogeneous swarm into a set of homogeneous collectives. We present theoretical results that show our approach is guaranteed to achieve complete segregation and validate our strategy in simulation and experiments.

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Shang, Beining, Richard M. Crowder, and Klaus-Peter Zauner. "An Approach to Sorting Swarm Robots to Optimize Performance." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59984.

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Swarm robotic systems can offer many advantages including robustness, flexibility and scalability. However one of the issues relating to overall swarm performance that needs to be considered is hardware variations inherent in the implementation of individual swarm robots. This variation can bring behavioral diversity within the swarm, resulting in uncontrollable swarm behaviors, low efficiency, etc. If swarm robots could be separated by behaviors, operational advantages could be obtained. In this paper we report an approach to the sorting of large robotic swarms using an approach inspired by chromatography. Hence the tedious and expensive calibration process can be avoided. The results investigate the influence of the internal control parameters, together with environmental effects on the robotic behavioral sorting. We concluded that if the robot has knowledge of previous events coupled with a specific arena pattern density will offer improved behavioral sorting.

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Lomuscio, Alessio, and Edoardo Pirovano. "Verifying Fault-Tolerance in Probabilistic Swarm Systems." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/46.

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We present a method for reasoning about fault-tolerance in unbounded robotic swarms. We introduce a novel semantics that accounts for the probabilistic nature of both the swarm and possible malfunctions, as well as the unbounded nature of swarm systems. We define and interpret a variant of probabilistic linear-time temporal logic on the resulting executions, including those arising from faulty behaviour by some of the agents in the swarm. We specify the decision problem of parameterised fault-tolerance, which concerns determining whether a probabilistic specification holds under possibly faulty behaviour. We outline a verification procedure that we implement and use to study a foraging protocol from swarm robotics, and report the experimental results obtained.

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McCullough, Paul, Mark Bacon, Nejat Olgac, and Daniel A. Sierra. "A Lyapunov Treatment of Swarm Coordination Under Conflict." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2509.

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This document considers hostile conflicts between two swarms, called pursuers and evaders, based on a double integrator model. In order to convert the marginally stable dynamics into stable-capture behavior, we introduce a control strategy based on the relative positions and velocities of opposing swarm members. To evaluate its effectiveness, a Lyapunov-based stability analysis is performed. For simplicity, this document considers swarms with equal membership strengths and equal mass only. The modeling is based on a set of suggested interaction force profiles, which are functions of local vectors. The group pursuit is conceived in two phases: the approach phase during which the two swarms act like two individuals; and the assigned pursuit phase where each pursuer is assigned to an evader.

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Harwell, John. "A Unified Mathematical Approach for Foraging and Construction Systems in a 1,000,000 Robot Swarm." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/908.

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Automation in construction is possible with systems designed using the swarm robotic principles of scalability, flexibility, robustness, and emergence. We derive quantitative measurements of these principles in 10,000 robot swarms as a first step in achieving this goal. We summarize our recent task allocation work in the context of an object gathering task and demonstrate its feasibility in the context of automated construction tasks. We present a trajectory to extend our current task allocation methodology using stochastic processes in order to present a unified approach to task allocation in swarm-robotic construction

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Reports on the topic "SWAAMI"

Ward, C. R., K. D. Peterson, L. J. Harpring, D. M. Immel, J. D. Jones, and W. R. Mallet. SWAMI II technology transfer plan. Office of Scientific and Technical Information (OSTI), December 1995. http://dx.doi.org/10.2172/385353.

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McCarthy, K. SWAMI, Stored Waste Autonomous Mobile Inspector. Office of Scientific and Technical Information (OSTI), November 1995. http://dx.doi.org/10.2172/120829.

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Howarth, Thomas R. SWAMSI Cymbals Projector. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada612404.

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Howarth, Thomas R. SWAMSI Cymbals Projector. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada541177.

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Hazen, F. B. The SWAMI inspection robot: Fernald site requirements. Office of Scientific and Technical Information (OSTI), September 1993. http://dx.doi.org/10.2172/10122150.

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D'Andrea, Raffaello. Control of Air Vehicle Swarms. Fort Belvoir, VA: Defense Technical Information Center, June 2008. http://dx.doi.org/10.21236/ada530333.

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Thompson, James. Spectra Swarm Evaluation. Office of Scientific and Technical Information (OSTI), February 2021. http://dx.doi.org/10.2172/1765853.

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Fahrig, W. F., and T. D. West. Diabase dyke swarms of the Canadian Shield. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/133917.

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Ouellett, Nicholas T. Laboratory and Modeling Studies of Insect Swarms. Fort Belvoir, VA: Defense Technical Information Center, February 2016. http://dx.doi.org/10.21236/ad1010208.

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Scarbrough, Kent, and Stephen K. Mitchell. SWAMSI: Bistatic CSAS and Target Echo Studies. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada569080.

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