ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network

This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.British Petroleum (98-A-1204); Defense Advanced Research Projects Agency (90-0083, 90-0175, 90-0128); National Science Foundation (IRI-90-00539); Army Research Office (DAAL-03-88-K0088

Fuzzy ARTMAP, Slow Learning and Probability Estimation

A nonparametric probability estimation procedure using the fuzzy ARTMAP neural network is here described. Because the procedure does not make a priori assumptions about underlying probability distributions, it yields accurate estimates on a wide variety of prediction tasks. Fuzzy ARTMAP is used to perform probability estimation in two different modes. In a 'slow-learning' mode, input-output associations change slowly, with the strength of each association computing a conditional probability estimate. In 'max-nodes' mode, a fixed number of categories are coded during an initial fast learning interval, and weights are then tuned by slow learning. Simulations illustrate system performance on tasks in which various numbers of clusters in the set of input vectors mapped to a given class.British Petroleum (89-A-1204); Defense Advanced Research Projects Agency (AFOSR-90-0083, ONR-N00014-92-J-4015); National Science Foundation (IRI-90-00530); Office of Naval Research (N00014-91-J-4100); Air Force Office of Scientific Research (90-1075

Near-Infrared Photometric Variability of Stars Toward the Orion A Molecular Cloud

We present an analysis of J, H, and K time series photometry obtained with the southern 2MASS telescope over a 0.84 x 6 deg^2 region centered near the Orion Nebula Cluster. These data are used to establish the near-infrared variability properties of pre-main-sequence stars in Orion on time scales of 1-36 days, 2 months, and 2 years. A total of 1235 variable stars are identified, ~93% of which are associated with the Orion A molecular cloud. The variable stars exhibit a diversity of photometric behavior with time, including cyclic fluctuations, aperiodic day-to-day fluctuations, eclipses, slow drifts in brightness over one month, colorless variability, stars that become redder as they fade, and stars that become bluer as they fade. We examine rotational modulation of cool and hot star spots, variable obscuration from an inner circumstellar disk, and changes in the mass accretion rate and other properties in a circumstellar disk as possible origins of the variability. Cool spots can explain the variability characteristics in 56-77% of the stars, while the properties of the photometric fluctuations are more consistent with hot spots or extinction changes in at least 23% of the stars, and with variations in the disk mass accretion rate or inner disk radius in 1% of our sample. However, differences between the details of the observations and the details of variability predicted these models suggest either that another variability mechanism not considered here may be operative, or that the observed variability represents the net results of several of these phenomena. Analysis of the star count data indicates that the ONC is part of a larger area of enhanced stellar surface density which extends over a 0.4 x 2.4 deg^2 (3.4 x 20 pc^2) region containing 2700 stars brighter than K=14. (abridged version)Comment: 75 pages with 27 figures; to appear in AJ; see also http://www.astro.caltech.edu/~jmc/variables/orio

Periodic Photometric Variability in the Becklin-Neugebauer Object

The Becklin-Neugebauer (BN) object in the Orion Nebula Cluster (ONC) is a well-studied optically invisible, infrared-bright young stellar object, thought to be an intermediate-mass protostar. We report here that BN exhibited nearly-sinusoidal periodic variability at the near-infrared H- and Ks-bands during a one month observing campaign in 2000 March/April. The period was 8.28 days and the peak-to-peak amplitude ~0.2 mag. Plausible mechanisms for producing the observed variability characteristics are explored.Comment: Accepted by ApJ Letter

Tenderization of Meat by Pre-rigor Infusion of Various Chelating Agent

Tenderness in meat is a most important characteristic. Meat that has acceptable color, finish and flavor will still be rejected if it is not tender. Tenderness is also a very elusive characteristic and difficult to evaluate. Objective measurements of tenderness have been devised in an attempt to associate tenderness with a more stable factor such as connective tissue, amount of finish, age and size of muscle fibers. These measurements are not entirely successful. Subjective measurements such as taste panels give a better indication of over-all acceptability of meat but do not yield a definite value for tenderness. Experiments on rigor in recent years seem to indicate that major differences in tenderness of meat are due to something inherent in the muscle protein rather than to other characteristics such as connective tissue and amount of finish. This study was designed to determine if tenderness of beef could be altered by the pre-rigor infusion of beef rounds with a solution of sodium hexametaphosphate (Calgon). The specific objectives of this study were: (1) to see if tenderness of beef was improved by pre-rigor infusion of beef rounds with a solution of Calgon; (2) to attempt to find other chelating compounds and the proper levels that would give the desired result of improved tenderness; (3) to determine the amount of glycogen in muscle at zero and 48 hours after slaughter; (4) to correlate shear values and taste panel scores for tenderness of the semimembranosis muscle; (5) to measure the extractable nitrogen in treated and control rounds 48 hours after slaughter and to correlate this extractable nitrogen with tenderness; (6) to correlate glycogen and lactic acid content of muscle 48 hours after slaughter. Fifty-four rabbits were used in this preliminary work in an attempt to determine compounds and levels which would produce the desired result of increased tenderness. In this study only the hind legs of the rabbit were used of which the left leg was used for treatment while the right leg was used for control. The rabbits were stunned with a sharp blow on back of the neck, bled immediately and the hind legs were skinned and removed at the femur bead. Care was taken to section the femoral artery two inches anterior to the main femoral artery branch and the cut end was clipped with a hemostat. Only the left leg was infused with chelating compound

ALMA Observations of Circumstellar Disks in the Upper Scorpius OB Association

We present ALMA observations of 106 G-, K-, and M-type stars in the Upper Scorpius OB Association hosting circumstellar disks. With these data, we measure the 0.88 mm continuum and $^{12}$CO $J$ = 3$-$2 line fluxes of disks around low-mass ($0.14-1.66$ $M_{\odot}$) stars at an age of 5-11 Myr. Of the 75 primordial disks in the sample, 53 are detected in the dust continuum and 26 in CO. Of the 31 disks classified as debris/evolved transitional disks, 5 are detected in the continuum and none in CO. The lack of CO emission in approximately half of the disks with detected continuum emission can be explained if CO is optically thick but has a compact emitting area ($\lesssim 40$ au), or if the CO is heavily depleted by a factor of at least $\sim1000$ relative to interstellar medium abundances and is optically thin. The continuum measurements are used to estimate the dust mass of the disks. We find a correlation between disk dust mass and stellar host mass consistent with a power-law relation of $M_{\mathrm{dust}}\propto M_*^{1.67\pm0.37}$. Disk dust masses in Upper Sco are compared to those measured in the younger Taurus star-forming region to constrain the evolution of disk dust mass. We find that the difference in the mean of $\log(M_{\mathrm{dust}}/M_*)$ between Taurus and Upper Sco is $0.64\pm0.09$, such that $M_{\mathrm{dust}}/M_*$ is lower in Upper Sco by a factor of $\sim4.5$.Comment: 18 pages of text, 11 Figures, 5 Tables. Published in Ap

Near-Infrared Photometric Variability of Stars Toward the Chamaeleon I Molecular Cloud

We present the results of a J, H, and K_s photometric monitoring campaign of a 0.72 x 6 sq deg. area centered on the Chamaeleon I star forming region. Data were obtained on 15 separate nights over a 4 month time interval using the 2MASS South telescope. Out of a total of 34,539 sources brighter than the photometric completeness limits (J=16.0, H=15.2, K_s=14.8), 95 exhibit near-infrared variability in one or more bands. The variables can be grouped into a population of bright, red objects that are associated with the Chamaeleon I association, and a population of faint, blue variables that are dispersed over the full 6 deg of the survey and are likely field stars or older pre-main-sequence stars unrelated to the present-day Chamaeleon I molecular cloud. Ten new candidate members of Chamaeleon I, including 8 brown dwarf candidates, have been identified based on variability and/or near-infrared excess emission in the J-H vs. H-K_s color-color-diagram. We also provide a compendium of astrometry and J, H, and K_s photometry for previously identified members and candidate members of Chamaeleon I.Comment: To appear in AJ; see http://www.astro.caltech.edu/~jmc/variables/cham1

The Spectroscopically Determined Substellar Mass Function of the Orion Nebula Cluster

We present a spectroscopic study of candidate brown dwarf members of the Orion Nebula Cluster (ONC). We obtained new J- and/or K-band spectra of ~100 objects within the ONC which are expected to be substellar based on their K,(H-K) magnitudes and colors. Spectral classification in the near-infrared of young low mass objects is described, including the effects of surface gravity, veiling due to circumstellar material, and reddening. From our derived spectral types and existing near-infrared photometry we construct an HR diagram for the cluster. Masses are inferred for each object and used to derive the brown dwarf fraction and assess the mass function for the inner 5.'1 x 5.'1 of the ONC, down to ~0.02 solar masses. The derived logarithmic mass function rises to a peak at ~0.2 solar masses, similar to previous IMF determinations derived from purely photometric methods, but falls off more sharply at the hydrogen-burning limit before leveling through the substellar regime. We compare the mass function derived here for the inner ONC to those presented in recent literature for the sparsely populated Taurus cloud members and the rich cluster IC 348. We find good agreement between the shapes and peak values of the ONC and IC 348 mass distributions, but little similarity between the ONC and Taurus results.Comment: Accepted for Publication in Apj. Added Erratu