Results for “Signalized Intersections” — Page 2

NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

NASA NTRSDate not supplied

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

NASA NTRS1982

Combinational logic for generating gate drive signals for phase control rectifiers

Control signals for phase-delay rectifiers, which require a variable firing angle that ranges from 0 deg to 180 deg, are derived from line-to-line 3-phase signals and both positive and negative firing angle control signals which are generated by comparing current command and actual current. Line-to-line phases are transformed into line-to-neutral phases and integrated to produce 90 deg phase delayed signals that are inverted to produce three cosine signals, such that for each its maximum occurs at the intersection of positive half cycles of the other two phases which are inputs to other inverters. At the same time, both positive and negative (inverted) phase sync signals are generated for each phase by comparing each with the next and producing a square wave when it is greater. Ramp, sync and firing angle controls signals are than used in combinational logic to generate the gate firing control signals SCR gate drives which fire SCR devices in a bridge circuit.

Dolland, C. R.↗

NASA NTRS1977

Infrared range sensor

Sensor employs triangulation technique to locate objects that lie in intersections of four emitted beams of light and fields of view of four phototransistors. Signals from individual phototransistors are filtered and identified by individual synchronous detectors, one for each beam-intersection point.

Hill, J. W.↗

NASA NTRS1992

Laboratory chamber experiments exploring the potential use of artificially ionized layers of gas as a Bragg reflector for over-the-horizon signals

A set of parallel plasma layers is generated by two intersecting microwave pulses in a chamber containing dry air at a pressure comparable to the upper atmosphere. The dependence of the breakdown conditions on the pressure and pulse length is examined. The results are shown to be consistent with the appearance of tail erosion of microwave pulse caused by air breakdown. Bragg scattering experiments, using the plasma layers as a Bragg reflector are then performed. Both time domain and frequency domain measurements of wave scattering are conducted. The experimental results are found to agree very well with the theory. Moreover, the time domain measurement of wave scattering provides an unambiguous way for determining the temporal evolution of electron density during the first 100-microsec period.

Kuo, S. P.↗

NASA NTRS1980

Interferometric locating system

A system is described for determining the position of a vehicle or other target that emits radio waves and which is of the type that senses the difference in time of arrival at spaced ground stations of signals from the vehicle to locate the vehicle on a set of intersecting hyperbolas. A network of four ground stations detects the radio emissions from the vehicle and by means of cross correlation derives the relative signal delay at the ground stations from which the vehicle position is deduced. Because the signal detection is by cross correlation, no knowledge of the emission is needed, which makes even unintentional radio noise emissions usable as a locator beacon. By positioning one of the four ground stations at an elevation significantly above the plane of the other three stations, a three dimensional fix on the vehicle is possible.

Macdoran, P. F.↗

NASA NTRS2002

Charge Generation and Propagation in Igneous Rocks

Various electrical phenomena have been reported prior to or concurrent with earthquakes such as resistivity changes, ground potentials, electromagnetic (EM), and luminous signals. Doubts have been raised as to whether some of these phenomena are real and indeed precursory. One of the reasons for uncertainty is that, despite decades of intense work, there is still no physically coherent model. Using low- to medium-velocity impacts to measure electrical signals with microsecond time resolution, it has now been observed that when dry gabbro and diorite cores are impacted at relatively low velocities, approximately 100 m/s, highly mobile charge carriers are generated in a small volume near the impact point. They spread through the rocks, causing electric potentials exceeding +400 mV, EM, and light emission. As the charge cloud spreads, the rock becomes momentarily conductive. When a dry granite block is impacted at higher velocity, approximately 1.5 km/s, the propagation of the P and S waves is registered through the transient piezoelectric response of quartz. After the sound waves have passed, the surface of the granite block becomes positively charged, suggesting the same charge carriers as observed during the low-velocity impact experiments, expanding from within the bulk. During the next 2-3 ms the surface potential oscillates, indicating pulses of electrons injected from ground and contact electrodes. The observations are consistent with positive holes, e.g., defect electrons in the O(2-) sublattice, traveling via the O 2p-dominated valence band of the silicate minerals. Before activation, the positive holes lay dormant in the form of electrically inactive positive hole pairs (PHP), chemically equivalent to peroxy links, O3X/OO\XO3, with X=Si(4+), Al(3+), etc. PHPs are introduced into the minerals by way of hydroxyl,O3X-OH, which all nominally anhydrous minerals incorporate when crystallizing in H2O-laden environments. The fact that positive holes can be activated by low-energy impacts, and their attendant sound waves, suggests that they can also be activated by microfracturing. Depending on where in the stressed rock volume the charge carriers are activated, they will form rapidly moving or fluctuating charge clouds that may account for earthquake-related electrical signals and EM emission. Wherever such charge clouds intersect the surface, high fields are expected, causing electric discharges and earthquake lights.

Freund, Friedemann↗

NASA NTRS1986

Thumb-actuated two-axis controller

A two axis joystick controller is described. It produces at least one output signal in relation to pivotal displacement of a member with respect to an intersection of the two axes. The member is pivotally movable on a support with respect to the two axes. The support has a centrally disposed aperture. A light source is mounted on the pivotally movable member above the aperture to direct light through the aperture. A light sensor is mounted below the aperture in the support at the intersection of the two axes to receive the light from the light source directed through the aperture. The light sensor produces at least one output signal related to a location on the sensor at which the light from the light source strikes the sensor.

Hollow, R. H.↗

NASA NTRS1982

Less-Costly Inertial Guidance

Two gyroscopes mounted in gimbals yield signals that allow calculation of velocity, position and altitude of an aircraft. The mass lowers center of gravity of gimbal-and-gyro assembly to below the intersection of their axes. Combination acts as a two-axis pendulum. Rate signals from the leveling gyroscope are integrated, amplified, and fed to gimbal torquers to restore pendulum to alinement with local vertical.

Merhav, S. J.↗

NASA NTRS1982

Synchronized voltage contrast display analysis system

An apparatus and method for comparing internal voltage potentials of first and second operating electronic components such as large scale integrated circuits (LSI's) in which voltage differentials are visually identified via an appropriate display means are described. More particularly, in a first embodiment of the invention a first and second scanning electron microscope (SEM) are configured to scan a first and second operating electronic component respectively. The scan pattern of the second SEM is synchronized to that of the first SEM so that both simultaneously scan corresponding portions of the two operating electronic components. Video signals from each SEM corresponding to secondary electron signals generated as a result of a primary electron beam intersecting each operating electronic component in accordance with a predetermined scan pattern are provided to a video mixer and color encoder.

Johnston, M. F.↗

NASA NTRS2002

Charge Resolution of the Silicon Matrix of the ATIC Experiment

ATIC (Advanced Thin Ionization Calorimeter) is a balloon borne experiment designed to measure the cosmic ray composition for elements from hydrogen to iron and their energy spectra from approx.50 GeV to near 100 TeV. It consists of a Si-matrix detector to determine the charge of a CRT particle, a scintillator hodoscope for tracking, carbon interaction targets and a fully active BGO calorimeter. ATIC had its first flight from McMurdo, Antarctica from 28/12/2000 to 13/01/2001. The ATIC flight collected approximately 25 million events. The silicon matrix of the ATIC spectrometer is designed to resolve individual elements from proton to iron. To provide this resolution careful calibration of each pixel of the silicon matrix is required. Firstly, for each electronic channel of the matrix the pedestal value was subtracted taking into account its drift during the flight. The muon calibration made before the flight was used then to convert electric signals (in ADC channel number) to energy deposits in each pixel. However, the preflight muon calibration was not accurate enough for the purpose, because of lack of statistics in each pixel. To improve charge resolution the correction was done for the position of Helium peak in each pixel during the flight . The other way to set electric signals in electronics channels of the Si-matrix to one scale was correction for electric channel gains accurately measured in laboratory. In these measurements it was found that small different nonlinearities for different channels are present in the region of charge Z > 20. The correction for these non-linearities was not done yet. In linear approximation the method provides practically the same resolution as muon calibration plus He-peak correction. For searching a pixel with the signal of primary particle an indication from the cascade in the calorimeter was used. For this purpose a trajectory was reconstructed using weight centers of energy deposits in BGO layers. The point of intersection of this trajectory with Si-matrix and its RMS was determined. The pixel with maximal signal in 3sigma region was taken as sought. The signal in this pixel was corrected by trajectory zenith angle. The preliminary results on charge resolution of the Si-matrix in the range from protons to iron are presented.

Zatsepin, V. I.↗

NASA NTRS2006

An Alternative for Emergency Preemption of Traffic Lights

An electronic communication-and-control system has been developed as a prototype of advanced means of automatically modifying the switching of traffic lights to give priority to emergency vehicles. This system could be used alternatively or in addition to other emergency traffic-light-preemption systems, including a variety of systems now in use as well as two proposed systems described in "Systems Would Preempt Traffic Lights for Emergency Vehicles" (NPO-30573), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 36. Unlike those prior systems that depend on detection of sounds and/or lights emitted by emergency vehicles, this system is not subject to severe range limitations. This system can be retrofitted into any pre-existing traffic-light-control system, without need to modify that system other than to make a minimal number of wire connections between the two systems. This system comprises several subsystems, including a transponder and interface circuitry on each emergency vehicle, a monitoring and control unit at each intersection equipped with traffic lights, and a wide-area two-way radio communication network that connects the emergency vehicles and intersection units. Computers in the various intersections and vehicle units run special-purpose software that implements the traffic- light-preemption scheme. The operations of the intersection and vehicle units are synchronized by use of Global Positioning System (GPS) timing signals. The transponder in each vehicle estimates its own position and velocity by use of GPS signals, deductive ("dead") reckoning, data from the onboard diagnostic (OBD) computer of the vehicle, and/or triangulation of beacon signals. When the operator of an emergency vehicle turns on its flashing lights and sirens in response to a request for an emergency response, the transponder unit goes into action, reading the OBD data to determine speed and acceleration, and reading and gathering further navigational data as described above. The position, velocity, and acceleration data are combined with vehicle-identification data in a prescribed format, and the resulting set of data is transmitted to the intersections within communication range of the transponder.

Foster, Conrad↗

NASA NTRS2000

Lidar Remote Sensing System

A lidar remote sensing system wherein a laser signal is transmitted along an optical path through a telescope having a primary and secondary mirrors and a rotating prism at the telescope output. When the reflected signal from the target is received it is passed back through the system to a detector, where it is heterodyned with a signal from a local oscillator to detect Doppler frequency shifts in the returned signal. Since the prism is rotating, the prism will be at one position when the signal is transmitted and at another when the returned signal is received. This causes the reflected signal to be off the optical path, reducing the power of the returned signal. To correct this problem a de-rotator or prism is mounted for rotation, in synchronism with the rotating prism. about the optical path in a position to intersect the returned beam and refract it back onto the optical path to reduce the power loss in the returned signal.

Michael J Kavaya↗

NASA NTRS2005

Emergency vehicle traffic signal preemption system

An emergency vehicle traffic light preemption system for preemption of traffic lights at an intersection to allow safe passage of emergency vehicles. The system includes a real-time status monitor of an intersection which is relayed to a communications controller for transmission to emergency vehicles as well as to a central dispatch office. The system also provides for audio warnings at an intersection to protect pedestrians who may not be in a position to see visual warnings or for various reasons cannot hear the approach of emergency vehicles. A transponder mounted on an emergency vehicle provides autonomous control so the vehicle operator can attend to getting to an emergency and not be concerned with the operation of the system. Activation of a Code 3 situation provides communications with each intersection being approached by an emergency vehicle and indicates whether the intersection is preempted or if there is any conflict with other approaching emergency vehicles. On-board diagnostics handle various information including heading, speed, and acceleration sent to a communications controller which is transmitted to an intersection and which also simultaneously receives information regarding the status of an intersection.

Bachelder, Aaron D.↗

NASA NTRS2011

Emergency vehicle traffic signal preemption system

An emergency vehicle traffic light preemption system for preemption of traffic lights at an intersection to allow safe passage of emergency vehicles. The system includes a real-time status monitor of an intersection which is relayed to a control module for transmission to emergency vehicles as well as to a central dispatch office. The system also provides for audio warnings at an intersection to protect pedestrians who may not be in a position to see visual warnings or for various reasons cannot hear the approach of emergency vehicles. A transponder mounted on an emergency vehicle provides autonomous control so the vehicle operator can attend to getting to an emergency and not be concerned with the operation of the system. Activation of a priority-code (i.e. Code-3) situation provides communications with each intersection being approached by an emergency vehicle and indicates whether the intersection is preempted or if there is any conflict with other approaching emergency vehicles. On-board diagnostics handle various information including heading, speed, and acceleration sent to a control module which is transmitted to an intersection and which also simultaneously receives information regarding the status of an intersection. Real-time communications and operations software allow central and remote monitoring, logging, and command of intersections and vehicles.

Bachelder, Aaron D.↗

NASA NTRS1979

Controller arm for a remotely related slave arm

A segmented controller arm configured and dimensioned to form a miniature kinematic replica of a remotely related slave arm is disclosed. The arm includes: (1) a plurality of joints for affording segments of the arm simultaneous angular displacement about a plurality of pairs of intersecting axes, (2) a plurality of position sensing devices for providing electrical signals indicative of angular displacement imparted to corresponding segments of the controller shaft about the axes, and (3) a control signal circuit for generating control signals to be transmitted to the slave arm. The arm is characterized by a plurality of yokes, each being supported for angular displacement about a pair of orthogonally related axes and counterbalanced against gravitation by a cantilevered mass.

Salisbury, J. K., Jr.↗

NASA NTRS2006

Engine spectrometer probe and method of use

The engine spectrometer probe and method of using the same of the present invention provides a simple engine spectrometer probe which is both lightweight and rugged, allowing an exhaust plume monitoring system to be attached to a vehicle, such as the space shuttle. The engine spectrometer probe can be mounted to limit exposure to the heat and debris of the exhaust plume. The spectrometer probe 50 comprises a housing 52 having an aperture 55 and a fiber optic cable 60 having a fiber optic tip 65. The fiber optic tip 65 has an acceptance angle 87 and is coupled to the aperture 55 so that the acceptance angle 87 intersects the exhaust plume 30. The spectrometer probe can generate a spectrum signal from light in the acceptance angle 506 and the spectrum signal can be provided to a spectrometer 508.

Barkhoudarian, Sarkis↗