Summary of the High Ice Water Content (HIWC) RADAR Flight Campaigns

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding and develop onboard weather radar processing to detect regions of high ice water content ahead of an aircraft and enable tactical avoidance of the potentially hazardous conditions. Both High Ice Water Content (HIWC) RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory which was equipped with a Honeywell RDR-4000 weather radar and icing instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results

A Survey of the Strategic Alternate Sourcing Program Offices Management of United States Air Force Diminishing Manufacturing Sources and Material Shortages Subject Matter Experts

The office designated by the Air Force to be DMSMS subject expert program office is known as the Strategic Alternate Sourcing Program Office (SASPO). Aided by the USAF Program Offices and DMSMS Subject Matter Experts, the SASPO is responsible for sourcing DMSMS resolutions as well as the organizing, training, and equipping of the Program Offices DMSMS Programs. Using quantitative research, this study conducts a survey, with the USAF Program Offices as the unit of analysis, to gain insight as to where the SASPO is doing well and where gaps exist in their program management. The analysis and conclusion identify where the SASPO should focus their attention to proactively manage DMSMS resolutions

Pilot fatigue detection using aircraft state variables

Pilot fatigue has been proven to be the cause of many aviation accidents. Fatigue introduces error into the pilot\u27s inputs, which can potentially lead to accidents. To date, fatigue has been widely researched through physiological variables and sleep studies. Often, systems monitoring physiological variables would require constant physical contact with the pilot during flight. This arrangement could be cumbersome to pilots, and may hinder their flying ability even more. These systems will also add unnecessary weight to the aircraft, which could lead to increases in fuel consumption. Sleep studies have been investigated in an attempt to determine causes of pilot fatigue based on the amount and quality of sleep they have received pre-flight, but they only serve for fatigue prevention purposes.;The main objective of this research effort is to show that separation between \u27rested\u27 and \u27tired\u27 pilot conditions can be put into evidence using parameters based on aircraft state and control variables and to design a fatigue detection scheme to determine the \u27on-line\u27 state of the pilot for a set of typical maneuvers.;Five pilots were instructed to fly a 6 degrees-of-freedom flight simulator through a given flight scenario under \u27rested\u27 and \u27tired\u27 conditions. State and control variables such as aircraft roll rate, angle of attack, elevator deflection, and others were recorded during flight. The desired values of these variables were determined depending on what maneuver the pilot was trying to accomplish. Steady state flight conditions and doublet inputs in still air and turbulence were considered in this study. Tracking errors were defined as the difference between the actual variable value and the desired value. Standard deviation and mean of the tracking errors were considered as candidate fatigue detectors and their performance was analyzed. The most promising detectors were then used to define composite detection parameters as weighted sums.;Two detection schemes were designed to determine the \u27rested\u27 or \u27tired\u27 state of the pilot based on comparing the composite parameter values to a threshold. The first scheme used heuristic and binary logic to define a series of rules hard coded through \u27if else\u27 statements capable of determining the pilot\u27s condition. The second detection scheme relied on fuzzy logic to make a \u27rested\u27 or \u27tired\u27 determination. Results showed that both schemes were capable of correctly classifying the condition of the pilot for many maneuvers. The detection schemes performed the best for the maneuvers performed in still air, but the detection rate was reduced when severe turbulence was present. A third approach of fatigue detection was investigated through implementation of a fuzzy neural network, and positive preliminary results deemed this method worthy of further exploration.;The analysis in this study presented compelling evidence that fatigue detection can be accomplished through the monitoring of aircraft state variables. Further research into using these detection schemes in conjunction with a flight compensation system may prove to be a viable, cost-effective intervention for reducing the number of accidents attributed to pilot fatigue

Visible Light Communication (VLC)

Visible light communication (VLC) using light-emitting diodes (LEDs) or laser diodes (LDs) has been envisioned as one of the key enabling technologies for 6G and Internet of Things (IoT) systems, owing to its appealing advantages, including abundant and unregulated spectrum resources, no electromagnetic interference (EMI) radiation and high security. However, despite its many advantages, VLC faces several technical challenges, such as the limited bandwidth and severe nonlinearity of opto-electronic devices, link blockage and user mobility. Therefore, significant efforts are needed from the global VLC community to develop VLC technology further. This Special Issue, “Visible Light Communication (VLC)”, provides an opportunity for global researchers to share their new ideas and cutting-edge techniques to address the above-mentioned challenges. The 16 papers published in this Special Issue represent the fascinating progress of VLC in various contexts, including general indoor and underwater scenarios, and the emerging application of machine learning/artificial intelligence (ML/AI) techniques in VLC

Radar Detection of High Concentrations of Ice Particles - Methodology and Preliminary Flight Test Results

High Ice Water Content (HIWC) has been identified as a primary causal factor in numerous engine events over the past two decades. Previous attempts to develop a remote detection process utilizing modern commercial radars have failed to produce reliable results. This paper discusses the reasons for previous failures and describes a new technique that has shown very encouraging accuracy and range performance without the need for any hardware modifications to industrys current radar designs. The performance of this new process was evaluated during the joint NASA/FAA HIWC RADAR II Flight Campaign in August of 2018. Results from that evaluation are discussed, along with the potential for commercial application, and development of minimum operational performance standards for a future commercial radar product

Summary of the High Ice Water Content (HIWC) RADAR Flight Campaigns

NASA and the FAA (Federal Aviation Administration) conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding and develop onboard weather radar processing to detect regions of high ice water content ahead of an aircraft and enable tactical avoidance of the potentially hazardous conditions. Both High Ice Water Content (HIWC) RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory which was equipped with a Honeywell RDR-4000 weather radar and icing instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 407)

This bibliography lists 289 reports, articles and other documents announced in the NASA Scientific and Technical Information System during Nov. 1995. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

TRIMAGE: A dedicated trimodality (PET/MR/EEG) imaging tool for schizophrenia

Simultaneous PET/MR/EEG (Positron Emission Tomography - Magnetic Resonance - Electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here within the framework of the European Union Project TRIMAGE. The trimodal, cost-effective PET/MR/EEG imaging tool makes use of cutting edge technology both in PET and in MR fields. A novel type of magnet (1.5T, non-cryogenic) has been built together with a PET scanner that makes use of the most advanced photodetectors (i.e., SiPM matrices), scintillators matrices (LYSO) and digital electronics. The combined PET/MR/EEG system is dedicated to brain imaging and has an inner diameter of 260 mm and an axial Field-of-View of 160 mm. It enables the acquisition and assessment of molecular metabolic information with high spatial and temporal resolution in a given brain simultaneously. The dopaminergic system and the glutamatergic system in schizophrenic patients are investigated via PET, the same physiological/pathophysiological conditions with regard to functional connectivity, via fMRI, and its electrophysiological signature via EEG. In addition to basic neuroscience questions addressing neurovascular-metabolic coupling, this new methodology lays the foundation for individual physiological and pathological fingerprints for a wide research field addressing healthy aging, gender effects, plasticity and different psychiatric and neurological diseases. The preliminary performances of two components of the imaging tool (PET and MR) are discussed. Initial results of the search of possible candidates for suitable schizophrenia biomarkers are also presented as obtained with PET/MR systems available to the collaboration

Stress, subjective wellbeing and self-knowledge in higher education teachers: A pilot study through bodyfulness approaches.

Work-related stress is a major cause of health problems worldwide. Faculty in educational institutions, including universities, also face high levels of stress, which undoubtedly affects their performance, level of personal satisfaction and wellbeing, and the relationship with students. Training interventions based on embodied learning can promote self-knowledge, emotional regulation and stress reduction, thereby increasing levels of psychological well-being. The present pilot study analyzed the impact of body awareness training in 31 university teachers using a controlled, randomized pre-post experimental design, with two experimental groups and a control group (n = 10). The two interventions were: Hatha Yoga (n = 11) and Dance Movement Therapy/Body Mind Centering (n = 10), which we have termed Body Movement Awareness. Variables related to body awareness, mindfulness, wellbeing, life satisfaction and stress were measured using self-perception tests. Cortisol levels, heart rate variability and sleep quality were also analyzed. Finally, participants’ reflections were analyzed according to a qualitative approach. The results showed significant differences between the control group and the Hatha Yoga group in terms of stress reduction and wellbeing. The Body Movement Awareness group exhibited evidence of contributions on self-knowledge, communication and kinesthetic empathy, key elements in the educational field. Despite the inherent limitations of the study, the conclusions are encouraging and open new lines of research from embodied approaches that introduce creative movement and group experience as part of the process of emotional regulation and self-knowledge.post-print2831 K