An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen\u27s self-organizing feature map, learning vector quantization, and a back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system

On-Line Free Form Surface Measurement Via a Fuzzy-Logic Controlled Scanning Probe

This paper presents a system and methodology for on-line free form surface measurement via a scanning contact probe installed on a CNC (computer numerical control) machine. The scanning probe provides more sampling points than any traditional touch trigger type of probes used on CNC machines, and better measuring accuracy than laser displacement sensing or structured lighting. The presented measuring system\u27s main advantage is that the number of measured points can vary with the change of surface curvature. To improve the measuring stability and continuity, fuzzy logic control, in lieu of traditional PID control, is employed. As a result, the system is capable of continuously detecting the boundaries of a measured object and measuring a relatively large complex surface. Based on the experimental results, the measuring accuracy is estimated between 20 and 30 μm (micrometers). In addition to surface measurement, the reconstructed surface data can be fed to a CAD/CAM system for component making or reproduction, which makes the reverse engineering of models comprised of free form surfaces readily accessible

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen\u27s self-organizing feature map, learning vector quantization, and a back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system

On-Line Free Form Surface Measurement Via a Fuzzy-Logic Controlled Scanning Probe

This paper presents a system and methodology for on-line free form surface measurement via a scanning contact probe installed on a CNC (computer numerical control) machine. The scanning probe provides more sampling points than any traditional touch trigger type of probes used on CNC machines, and better measuring accuracy than laser displacement sensing or structured lighting. The presented measuring system\u27s main advantage is that the number of measured points can vary with the change of surface curvature. To improve the measuring stability and continuity, fuzzy logic control, in lieu of traditional PID control, is employed. As a result, the system is capable of continuously detecting the boundaries of a measured object and measuring a relatively large complex surface. Based on the experimental results, the measuring accuracy is estimated between 20 and 30 μm (micrometers). In addition to surface measurement, the reconstructed surface data can be fed to a CAD/CAM system for component making or reproduction, which makes the reverse engineering of models comprised of free form surfaces readily accessible

Data Communication Between an Expert System Shell and a Conventional Algorithmic Program With Application to Cam Motion Specification

Although more and more expert system shells have begun to provide communication interfaces to conventional procedural languages, the interfaces are basically shell- and language-dependent. This paper presents a simple, shell- and language-independent data communication technique between a shell and a procedural language via a concept analogous to the handshake data transmission used in microprocessors. A control file is used for the action of handshake. The communication interface is between two data files in two different language environments. A program written in a LISP-based expert system shell, OPS 5, and one written in a procedural language, FORTRAN, were tested to verify the presented technique. An expert system for cam motion specification, which needs the following three tasks—symbolic representation, numerical computation, and their communication—is described as one of the possible applications of the technique. These three tasks are essential to automated engineering design and analysis

Data Communication Between an Expert System Shell and a Conventional Algorithmic Program With Application to Cam Motion Specification

Although more and more expert system shells have begun to provide communication interfaces to conventional procedural languages, the interfaces are basically shell- and language-dependent. This paper presents a simple, shell- and language-independent data communication technique between a shell and a procedural language via a concept analogous to the handshake data transmission used in microprocessors. A control file is used for the action of handshake. The communication interface is between two data files in two different language environments. A program written in a LISP-based expert system shell, OPS 5, and one written in a procedural language, FORTRAN, were tested to verify the presented technique. An expert system for cam motion specification, which needs the following three tasks—symbolic representation, numerical computation, and their communication—is described as one of the possible applications of the technique. These three tasks are essential to automated engineering design and analysis

An Efficient Technique for Finding the Desired Global Optimum of Robotic Joint Displacement

For an industrial robot on a daily operation basis such as pick and place, it is desired to minimize the robotic joint displacements when moving the robot from one location to another. The objective of the optimization here is to simultaneously minimize a robot end effector\u27s positional error and the robotic joint displacements. By modifying the searching algorithm in the existing complex optimization method, this article presents a technique for finding the desired global optimum solution more efficiently. To compare the optimum searching capability between the proposed and existing searching algorithms, a modified Himmelblau\u27s function is used as an objective function. The presented technique is then applied to a spatial three-link robot manipulator for global minimization of the joint displacements

The Luminosity Function of Galaxies in the Las Campanas Redshift Survey

We present the $R$-band luminosity function for a sample of 18678 galaxies, with average redshift $z = 0.1$, from the Las Campanas Redshift Survey. The luminosity function may be fit by a Schechter function with $M^* = -20.29 \pm 0.02 + 5 \log h$, $\alpha = -0.70 \pm 0.05$, and $\phi^* = 0.019 \pm 0.001 \ h^3$~Mpc$^{-3}$, for absolute magnitudes$-23.0 \leq M - 5 \log h \leq -17.5$. We compare our luminosity function to that from other redshift surveys; in particular our normalization is consistent with that of the Stromlo-APM survey, and is therefore a factor of two below that implied by the$b_J \approx 20$bright galaxy counts. Our normalization thus indicates that much more evolution is needed to match the faint galaxy count data, compared to minimal evolution models which normalize at$b_J \approx 20$. Also, we show that our faint-end slope$\alpha = -0.7$, though ``shallower'' than typical previous values$\alpha = -1$, results primarily from fitting the detailed shape of the LCRS luminosity function, rather than from any absence of intrinsically faint galaxies from our survey. Finally, using [OII] 3727 equivalent width$W_{\lambda} = 5$~\AA \ as the dividing line, we find significant differences in the luminosity functions of emission and non-emission galaxies, particularly in their$\alpha$values. Emission galaxies have Schechter parameters$M^* = -20.03 \pm 0.03 + 5 \log h$and$\alpha = -0.9 \pm 0.1$, while non-emission galaxies are described by$M^* = -20.22 \pm 0.02 + 5 \log h$and$\alpha = -0.3 \pm 0.1$. (abridged abstract)Comment: 41 pages, including 13 postscript figures, uses AASTEX v4.0 style files. Important clarification of R-band definition, plus correction of luminosity densities and updated references. Main conclusions unchanged. Final version to appear in Ap

The Taiwan ECDFS Near-Infrared Survey: Ultra-deep J and Ks Imaging in the Extended Chandra Deep Field-South

We present ultra-deep J and Ks imaging observations covering a 30' * 30' area of the Extended Chandra Deep Field-South (ECDFS) carried out by our Taiwan ECDFS Near-Infrared Survey (TENIS). The median 5-sigma limiting magnitudes for all detected objects in the ECDFS reach 24.5 and 23.9 mag (AB) for J and Ks, respectively. In the inner 400 arcmin^2 region where the sensitivity is more uniform, objects as faint as 25.6 and 25.0 mag are detected at 5-sigma. So this is by far the deepest J and Ks datasets available for the ECDFS. To combine the TENIS with the Spitzer IRAC data for obtaining better spectral energy distributions of high-redshift objects, we developed a novel deconvolution technique (IRACLEAN) to accurately estimate the IRAC fluxes. IRACLEAN can minimize the effect of blending in the IRAC images caused by the large point-spread functions and reduce the confusion noise. We applied IRACLEAN to the images from the Spitzer IRAC/MUSYC Public Legacy in the ECDFS survey (SIMPLE) and generated a J+Ks selected multi-wavelength catalog including the photometry of both the TENIS near-infrared and the SIMPLE IRAC data. We publicly release the data products derived from this work, including the J and Ks images and the J+Ks selected multiwavelength catalog.Comment: 25 pages, 25 figures, ApJS in pres