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At least 289 records · Page 16

Imaginaries of the Pandemic in Chile: A Conceptual‐Empirical Discussion

This article aims to reconstruct the social imaginaries of Coronavirus disease 2019 (COVID‐19) in Chile. We seek to understand how families interpret their experience confronting the pandemic by identifying four main aspects: (a) the COVID‐19 pandemic, (b) working and learning, (c) health and (d) family life. Following Habermas' distinction between lifeworld and social systems, we consider these issues as constituting the social imaginary of lifeworld, different but related to the imaginaries of social systems. The qualitative empirical data was gathered through a sample of 38 families interviewed online between September 2020 and January 2021 in four Chilean cities: Iquique, Valparaíso, Santiago and Concepción. Other complementary sources of information are multimodal ethnography (digital diaries), press articles and state reports.

Vergara, Jorge Iván↗

Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models

Software flaw detection using multimodal deep learning models has been demonstrated as a very competitive approach on benchmark problems. In this work, we demonstrate that even better performance can be achieved using neural architecture search (NAS) combined with multimodal learning models. We adapt a NAS framework aimed at investigating image classification to the problem of software flaw detection and demonstrate improved results on the Juliet Test Suite, a popular benchmarking data set for measuring performance of machine learning models in this problem domain.

97 MATHEMATICS AND COMPUTING↗

Electronic readout systems for microchannel plates

The modes of operation of position-sensitive electronic readout systems which use high-gain microchannel plate (MCP) electron multipliers are described, and their performance characteristics, along with those of the MCP, are compared. Among the structures presented are the wedge-and-strip, Codacon, and multilayer coincidence-anode MAMA (Multimode Microchannel Array) arrays. Spatial resolution of 25 x 25 sq microns (coincidence anode arrays) is achieved with an array format of 256 x 1024 pixels. On the basis of the performance data it is concluded that the readout systems using only conducting electrodes offer the best performance characteristics.

Timothy, J. G.↗

Real-time artificial intelligence issues in the development of the adaptive tactical navigator

Adaptive Tactical Navigation (ATN) is a laboratory prototype of a knowledge based system to provide navigation system management and decision aiding in the next generation of tactical aircraft. ATN's purpose is to manage a set of multimode navigation equipment, dynamically selecting the best equipment to use in accordance with mission goals and phase, threat environment, equipment malfunction status, and battle damage. ATN encompasses functions as diverse as sensor data interpretation, diagnosis, and planning. Real time issues that were identified in ATN and the approaches used to address them are addressed. Functional requirements and a global architecture for the ATN system are described. Decision making with time constraints are discussed. Two subproblems are identified; making decisions with incomplete information and with limited resources. Approaches used in ATN to address real time performance are described and simulation results are discussed.

Green, Peter E.↗

Robotic vision/sensing for space applications

A review is presented of efforts currently in progress at the NASA/Johnson Space Center and Rice University, the accomplishments to date, and some of the anticipated future developments. Both systems and algorithms are discussed. The evolution of future vision/sensing is projected to included the fusion of multisensors ranging from microwave to optical with multimode capability to include position, attitude, recognition, and motion parameters. The algorithms for information extraction are expected to incorporate aspects of intelligence and knowledge for the interpolation and extrapolation of the needed data. The key features of the overall system design will be small size and weight, fast signal processing, robust algorithms, and accurate parameter determination. These aspects of vision/sensing are also discussed.

Krishen, Kumar↗

Perl Tools for Automating Satellite Ground Systems

The freeware scripting language Pert offers many opportunities for automating satellite ground systems for new satellites as well as older, in situ systems. This paper describes a toolkit that has evolved from of the experiences gained by using Pert to automate the ground system for the Compton Gamma Ray Observatory (CGRO) and for automating some of the elements in the Earth Observing System Data and Operations System (EDOS) ground system at Goddard Space Flight Center (GSFC). CGRO is an older ground system that was forced to automate because of fund cuts. Three 8 hour shifts were cut back to one 8 hour shift, 7 days per week. EDOS supports a new mission called Terra, launched December 1999 that requires distribution and tracking of mission-critical reports throughout the world. Both of these ground systems use Pert scripts to process data and display it on the Internet as well as scripts to coordinate many of the other systems that make these ground systems work as a coherent whole. Another task called Automated Multimodal Trend Analysis System (AMTAS) is looking at technology for isolation and recovery of spacecraft problems. This effort has led to prototypes that seek to evaluate various tools and technology that meet at least some of the AMTAS goals. The tools, experiences, and lessons learned by implementing these systems are described here.

McLean, David↗

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of a satellite microwave radiometer to sense the surface temperature of the world oceans

A proposed S-band radiometer for determining the ocean surface temperature with an absolute accuracy of + or - 1 Kelvin and a resolution of + or - .1 Kelvin was placed under the Advanced Applications Flight Experiment for further development into Nimbus readiness state. The results of assessing the following are described: effects due to the state of the sea surface, effects caused by the intervening atmosphere, and effects associated with imperfections in the instrument itself. An extensive sea truth program is also described for correlation of aircraft test flight measurements or of satellite remote measurement to in-situ data. An improved radiometer design is a modified Dicke-switch type with temperature stabilized, microwave integrated circuit, front-end and with a pulsed injection-noise nulling system. The radiometer has a multimode rectangular horn antenna with very low ohmic losses and a beam efficiency of 98% or better.

Hidy, G. M.↗

Multimodal CO2 Transportation Cost Model

This model provides a cost estimate for transporting CO2 via truck or rail in the United States using commercially available equipment and technologies. The model includes an analysis of direct and indirect CO2 emissions to determine costs per net tonne of CO2 transported. Publicly available data and methods published in the peer-reviewed literature are used to the extent possible; references are available at the bottom of the "Calculations" sheet. Upstream (i.e., liquefaction, buffer storage) and downstream (i.e., buffer storage, reconditioning) activities are included in the model of emissions and costs. All capital and operating expenditures are estimated in the "Calculations" sheet. The cost of financing the project is determined in the "FINEX" sheet. All user inputs are done via drop down menus in on the "User Interface" sheet. Summary results are also provided on the "User Interface" sheet.

Myers, CoreyA↗

Multifunction Imaging and Spectroscopic Instrument

A proposed optoelectronic instrument would perform several different spectroscopic and imaging functions that, heretofore, have been performed by separate instruments. The functions would be reflectance, fluorescence, and Raman spectroscopies; variable-color confocal imaging at two different resolutions; and wide-field color imaging. The instrument was conceived for use in examination of minerals on remote planets. It could also be used on Earth to characterize material specimens. The conceptual design of the instrument emphasizes compactness and economy, to be achieved largely through sharing of components among subsystems that perform different imaging and spectrometric functions. The input optics for the various functions would be mounted in a single optical head. With the exception of a targeting lens, the input optics would all be aimed at the same spot on a specimen, thereby both (1) eliminating the need to reposition the specimen to perform different imaging and/or spectroscopic observations and (2) ensuring that data from such observations can be correlated with respect to known positions on the specimen. The figure schematically depicts the principal components and subsystems of the instrument. The targeting lens would collect light into a multimode optical fiber, which would guide the light through a fiber-selection switch to a reflection/ fluorescence spectrometer. The switch would have four positions, enabling selection of spectrometer input from the targeting lens, from either of one or two multimode optical fibers coming from a reflectance/fluorescence- microspectrometer optical head, or from a dark calibration position (no fiber). The switch would be the only moving part within the instrument.

Mouroulis, Pantazis↗

Interactive multi-spectral analysis of more than one Sonrai village in Niger, West Africa

Use of LANDSAT data and an interaction system is considered for identifying and measuring small scale compact human settlements (villages) for demographic and anthropological studies. Because village components are not uniformly distributed within any one village, they apparently are multimodal, spectrally. Therefore, the functions of location and enumeration are kept separate. Measurement of a known village is compared with CCT response.

Reining, P.↗

Progress on Understanding Rayleigh–Taylor Flow and Mixing Using Synergy Between Simulation, Modeling, and Experiment

Simultaneous advances in numerical methods and computing, theoretical techniques, and experimental diagnostics have all led independently to better understanding of Rayleigh–Taylor (RT) instability, turbulence, and mixing. In particular, experiments have provided significant motivation for many simulation and modeling studies, as well as validation data. Numerical simulations have also provided data that is not currently measurable or very difficult to measure accurately in RT unstable flows. Thus, simulations have also motivated new measurements in this class of buoyancy-driven flows. This overview discusses simulation and modeling studies synergistic with experiments and examples of how experiments have motivated simulations and models of RT instability, flow, and mixing. First, a brief summary of measured experimental and calculated simulation quantities, of experimental approaches, and of issues and challenges in the simulation and modeling of RT experiments is presented. Implicit large-eddy, direct numerical, and large-eddy simulations validated using RT experimental data are then discussed. This is followed by a discussion of modeling using analytical, modal, buoyancy–drag, and turbulent transport models of RT mixing experiments. The discussion will focus on three-dimensional RT mixing arising from multimode perturbations. Finally, this focused review concludes with a perspective on future simulation, modeling, and experimental directions for further research. Research in simulation and modeling of RT unstable flows, coupled with experiments, has made significant progress over the past several decades. This overview serves as an opportunity to both discuss progress and to stimulate future research on simulation and modeling of this unique class of hydrodynamically unstable turbulent flows.

42 ENGINEERING↗

Design of fiber optic probes for laser light scattering

A quantitative analysis is presented of the role of optical fibers in laser light scattering. Design of a general fiber optic/microlens probe by means of ray tracing is described. Several different geometries employing an optical fiber of the type used in lightwave communications and a graded index microlens are considered. Experimental results using a nonimaging fiber optic detector probe show that due to geometrical limitations of single mode fibers, a probe using a multimode optical fiber has better performance, for both static and dynamic measurements of the scattered light intensity, compared with a probe using a single mode fiber. Fiber optic detector probes are shown to be more efficient at data collection when compared with conventional approaches to measurements of the scattered laser light. Integration of fiber optic detector probes into a fiber optic spectrometer offers considerable miniaturization of conventional light scattering spectrometers, which can be made arbitrarily small. In addition static and dynamic measurements of scattered light can be made within the scattering cell and consequently very close to the scattering center.

Dhadwal, Harbans S.↗

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗

Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control modes that are selected according to some performance or operational criteria. As the engine degrades, parameters shift from their nominal values. Thus, when a new control mode is swapped in, a variable that is being brought under control might have an excessive initial error. The new adaptive algorithm adjusts the controller gains on the basis of the level of degradation to minimize the disruptive influence of the large error on other variables and to recover the desired thrust response.

Litt, Jonathan S.↗

Mind the gap: Bridging the divide between AI aspirations and the reality of autonomous microscopy

What does materials science look like in the “Age of Artificial Intelligence?” Each material’s domain—synthesis, characterization, and modeling—has a different answer to this question, motivated by unique challenges and constraints. This work focuses on the tremendous potential of autonomous characterization within electron microscopy. We present our recent advancements in developing domain-aware, multimodal models for microscopy analysis capable of describing complex atomic systems. We then address the critical gap between the theoretical promise of autonomous microscopy and its current practical limitations, showcasing recent successes while highlighting the necessary developments to achieve robust, real-world autonomy.

2D materials↗