Power assist EVA glove development

Structural modeling of the EVA glove indicates that flexibility in the metacarpophalangeal (MCP) joint can be improved by selectively lowering the elasticity of the glove fabric. Two strategies are used to accomplish this. One method uses coil springs on the back of the glove to carry the tension in the glove skin due to pressurization. These springs carry the loads normally borne by the glove fabric, but are more easily deformed. An active system was also designed for the same purpose and uses gas filled bladders attached to the back of the EVA glove that change the dimensions of the back of the glove and allow the glove to bend at the MCP joint, thus providing greater flexibility at this joint. A threshold control scheme was devised to control the action of the joint actuators. Input to the controller was provided by thin resistive pressure sensors placed between the hand and the pressurized glove. The pressure sensors consist of a layer of polyester film that has a thin layer of ink screened on the surface. The resistivity of the ink is pressure dependent, so an extremely thin pressure sensor can be fabricated by covering the ink patch with another layer of polyester film and measuring the changing resistance of the ink with a bridge circuit. In order to sense the force between the hand and the glove at the MCP joint, a sensor was placed on the palmar face of the middle finger. The resultant signal was used by the controller to decide whether to fill or exhaust the bladder actuators on the back of the glove. The information from the sensor can also be used to evaluate the effectiveness of a given control scheme or glove design since the magnitude of the measured pressures gives some idea of the torque required to bend a glove finger at the MCP joint. Tests of this actuator, sensor, and control system were conducted in an 57.2 kPa glove box by performing a series of 90 degree finger bends with a glove without an MCP joint assembly, a glove with the coil spring assembly, and with the four fingered actuated glove. The tests of these three glove designs confirm the validity of the model

A preliminary structural analysis of space-based inflatable tubular frame structures

The use of inflatable structures has often been proposed for aerospace and planetary applications. The advantages of such structures include low launch weight and easy assembly. The use of inflatables for applications requiring very large frame structures intended for aerospace use are proposed. In order to consider using an inflated truss, the structural behavior of the inflated frame must be examined. The statics of inflated tubes as beams was discussed in the literature, but the dynamics of these elements has not received much attention. In an effort to evaluate the vibration characteristics of the inflated beam a series of free vibration tests of an inflated fabric cantilevers were performed. Results of the tests are presented and models for system behavior posed

A feasibility study of hand kinematics for EVA analysis using magnetic resonance imaging

A new method of analyzing the kinematics of joint motion is developed. Magnetic Resonance Imaging (MRI) offers several distinct advantages. Past methods of studying anatomic joint motion have usually centered on four approaches. These methods are x-ray projection, goniometric linkage analysis, sonic digitization, and landmark measurement of photogrammetry. Of these four, only x-ray is applicable for in vivo studies. The remaining three methods utilize other types of projections of inter-joint measurements, which can cause various types of error. MRI offers accuracy in measurement due to its tomographic nature (as opposed to projection) without the problems associated with x-ray dosage. Once the data acquisition of MR images was complete, the images were processed using a 3D volume rendering workstation. The metacarpalphalangeal (MCP) joint of the left index finger was selected and reconstructed into a three-dimensional graphic display. From the reconstructed volumetric images, measurements of the angles of movement of the applicable bones were obtained and processed by analyzing the screw motion of the MCP joint. Landmark positions were chosen at distinctive locations of the joint at fixed image threshold intensity levels to ensure repeatability. The primarily two dimensional planar motion of this joint was then studied using a method of constructing coordinate systems using three (or more) points. A transformation matrix based on a world coordinate system described the location and orientation of a local target coordinate system. Future research involving volume rendering of MRI data focusing on the internal kinematics of the hand's individual ligaments, cartilage, tendons, etc. will follow. Its findings will show the applicability of MRI to joint kinematics for gaining further knowledge of the hand-glove (power assisted) design for extravehicular activity (EVA)

EVA Glove Research Team

The goal of the basic research portion of the extravehicular activity (EVA) glove research program is to gain a greater understanding of the kinematics of the hand, the characteristics of the pressurized EVA glove, and the interaction of the two. Examination of the literature showed that there existed no acceptable, non-invasive method of obtaining accurate biomechanical data on the hand. For this reason a project was initiated to develop magnetic resonance imaging as a tool for biomechanical data acquisition and visualization. Literature reviews also revealed a lack of practical modeling methods for fabric structures, so a basic science research program was also initiated in this area

Recent Transits of the Super-Earth Exoplanet GJ 1214b

We report recent ground-based photometry of the transiting super-Earth exoplanet GJ1214b at several wavelengths, including the infrared near 1.25 microns (J-band). We observed a J-band transit with the FLAMINGOS infrared imager and the 2.1-meter telescope on Kitt Peak, and we observed several optical transits using a 0.5-meter telescope on Kitt Peak and the 0.36-meter Universidad de Monterrey Observatory telescope. Our high-precision J-band observations exploit the brightness of the M-dwarf host star at this infrared wavelength as compared to the optical, as well as being significantly less affected by stellar activity and limb darkening. We fit the J-band transit to obtain an independent determination of the planetary and stellar radii. Our radius for the planet (2.61^+0.30_-0.11 Earth radii) is in excellent agreement with the discovery value reported by Charbonneau et al. based on optical data. We demonstrate that the planetary radius is insensitive to degeneracies in the fitting process. We use all of our observations to improve the transit ephemeris, finding P=1.5804043 +/- 0.0000005 days, and T0=2454964.94390 +/- 0.00006 BJD.Comment: Accepted for ApJ Letters, 7 pages, 3 Figures, 2 Table

Remote Sensing of Coniferous Forest Leaf Area

Many important ecological questions concern ecosystem processes occurring over large areas. However, our understanding o f ecosystem functions is derived primarily from research executed on small, intensively studied sites, and extrapolation to large areas is difficult

Malware Type Recognition and Cyber Situational Awareness

Current technologies for computer network and host defense do not provide suitable information to support strategic and tactical decision making processes. Although pattern-based malware detection is an active research area, the additional context of the type of malware can improve cyber situational awareness. This additional context is an indicator of threat capability thus allowing organizations to assess information losses and focus response actions appropriately. Malware Type Recognition (MaTR) is a research initiative extending detection technologies to provide the additional context of malware types using only static heuristics. Test results with MaTR demonstrate over a 99% accurate detection rate and 59% test accuracy in malware typing

Malware Target Recognition via Static Heuristics

Organizations increasingly rely on the confidentiality, integrity and availability of their information and communications technologies to conduct effective business operations while maintaining their competitive edge. Exploitation of these networks via the introduction of undetected malware ultimately degrades their competitive edge, while taking advantage of limited network visibility and the high cost of analyzing massive numbers of programs. This article introduces the novel Malware Target Recognition (MaTR) system which combines the decision tree machine learning algorithm with static heuristic features for malware detection. By focusing on contextually important static heuristic features, this research demonstrates superior detection results. Experimental results on large sample datasets demonstrate near ideal malware detection performance (99.9+% accuracy) with low false positive (8.73e-4) and false negative rates (8.03e-4) at the same point on the performance curve. Test results against a set of publicly unknown malware, including potential advanced competitor tools, show MaTR’s superior detection rate (99%) versus the union of detections from three commercial antivirus products (60%). The resulting model is a fine granularity sensor with potential to dramatically augment cyberspace situation awareness