Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

A set of training statistics for the 30 meter resolution simulated thematic mapper MSS data was generated based on land use/land cover classes. In addition to this supervised data set, a nonsupervised multicluster block of training statistics is being defined in order to compare the classification results and evaluate the effect of the different training selection methods on classification performance. Two test data sets, defined using a stratified sampling procedure incorporating a grid system with dimensions of 50 lines by 50 columns, and another set based on an analyst supervised set of test fields were used to evaluate the classifications of the TMS data. The supervised training data set generated training statistics, and a per point Gaussian maximum likelihood classification of the 1979 TMS data was obtained. The August 1980 MSS data was radiometrically adjusted. The SAR data was redigitized and the SAR imagery was qualitatively analyzed

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Separate holograms of horizontally (HH) and vertically (HV) polarized responses obtained by the APQ-102 side-looking radar were processed through an optical correlator and the resulting image was recorded on positive film from which black and white negative and positive prints were made. Visual comparison of the HH and HV images reveals a distinct dark band in the imagery which covers about 30% of the radar strip. Preliminary evaluaton of the flight line 1 date indicates that various features on the HH and HV images seem to have different response levels. The amount of sidelap due to the look angle between flight lines 1 and 2 is negligible. NASA mission #425 to obtain flightlines of NS-001 MSS data and supporting aerial photography was successfully flown. Flight line 3 data are of very good quality and virtually cloud-free. Results of data analysis for selection of test fields and for evaluation of waveband combination and spatial resolution are presented

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented

Agricultural scene understanding

The author has identified the following significant results. The LACIE field measurement data were radiometrically calibrated. Calibration enabled valid comparisons of measurements from different dates, sensors, and/or locations. Thermal band canopy results included: (1) Wind velocity had a significant influence on the overhead radiance temperature and the effect was quantized. Biomass and soil temperatures, temperature gradient, and canopy geometry were altered. (2) Temperature gradient was a function of wind velocity. (3) Temperature gradient of the wheat canopy was relatively constant during the day. (4) The laser technique provided good quality geometric characterization

An interdisciplinary analysis of ERTS data for Colorado mountain environments using ADP techniques. An early analysis of ERTS-1 data

There are no author-identified significant results in this report. The principal problem encountered has been the lack of good quality, small scale baseline photography for the test areas. Analysis of the ERTS-1 data for the San Juan Site will emphasize development of a preliminary spectral classification defining grass cover categories, and then selection of subframes for intensive investigation of the forestry, geologic, and hydrologic properties of the area. Primary work has been devoted to the selection and digitization of areas for topographic modeling, and compilation of ground based data maps necessary for computer analysis. Study effort has emphasized: geomorphic features; macro-vegetation; micro-vegetation; snow-hydrology; insect/disease damage; and blow-down. Analysis of a frame of the Lake Texoma area indicates a great deal of potential in the analysis and interpretation of ERTS imagery. Preliminary results of investigations of geologic, forest, range, cropland, and water resources of the area are summarized

Patterns of Pupillary Activity During Binocular Disparity Resolution

This study examined the dynamic coordination between disconjugate, vergence eye movements, and pupil size in 52 normal subjects during binocular disparity stimulation in a virtual reality display. Eye movements and pupil area were sampled with a video-oculographic system at 100 Hz during performance of two tasks, (1) fusion of a binocular disparity step (±1.5° of visual angle in the horizontal plane) and (2) pursuit of a sinusoidally varying binocular disparity stimulus (0.1 Hz, ±2.6° of visual angle in the horizontal plane). Pupil size data were normalized on the basis of responses to homogeneous illumination increments ranging from 0.42 to 65.4 cd/m2. The subjects produced robust vergence eye movements in response to disparity step shifts and high fidelity sinusoidal vergence responses (R2 relative to stimulus profile: 0.933 ± 0.088), accompanied by changes in pupil area. Trajectory plots of pupil area as a function of vergence angle showed that the pupil area at zero vergence is altered between epochs of linear vergence angle—pupil area relations. Analysis with a modified Gath-Geva clustering algorithm revealed that the dynamic relationship between the ocular vergence angle and pupil size includes two different transient, synkinetic response patterns. The near response pattern, pupil constriction during convergence and pupil dilation during divergence, occurred ~80% of the time across subjects. An opposite, previously undescribed synkinetic pattern was pupil constriction during divergence and pupil dilatation during convergence; it occurred ~15% of the time across subjects. The remainder of the data were epochs of uncorrelated activity. The pupil size intercepts of the synkinetic segments, representing pupil size at initial tropia, had different relationships to vergence angle for the two main coordinated movement types. Hippus-like movements of the pupil could also be accompanied by vergence movements. No pupil coordination was observed during a conjugate pursuit task. In terms of the current dual interaction control model (1), findings suggest that the synkinetic eye and pupillary movements are produced by a dynamic switch of the influence of vergence related information to pupil control, accompanied by a resetting of the pupil aperture size at zero-vergence

Offline Signature Verification by Combining Graph Edit Distance and Triplet Networks

Biometric authentication by means of handwritten signatures is a challenging pattern recognition task, which aims to infer a writer model from only a handful of genuine signatures. In order to make it more difficult for a forger to attack the verification system, a promising strategy is to combine different writer models. In this work, we propose to complement a recent structural approach to offline signature verification based on graph edit distance with a statistical approach based on metric learning with deep neural networks. On the MCYT and GPDS benchmark datasets, we demonstrate that combining the structural and statistical models leads to significant improvements in performance, profiting from their complementary properties

Local modes, phonons, and mass transport in solid 4^4He

We propose a model to treat the local motion of atoms in solid $^{4}$He as a local mode. In this model, the solid is assumed to be described by the Self Consistent Harmonic approximation, combined with an array of local modes. We show that in the bcc phase the atomic local motion is highly directional and correlated, while in the hcp phase there is no such correlation. The correlated motion in the bcc phase leads to a strong hybridization of the local modes with the T$_{1}(110)$ phonon branch, which becomes much softer than that obtained through a Self Consistent Harmonic calculation, in agreement with experiment. In addition we predict a high energy excitation branch which is important for self-diffusion. Both the hybridization and the presence of a high energy branch are a consequence of the correlation, and appear only in the bcc phase. We suggest that the local modes can play the role in mass transport usually attributed to point defects (vacancies). Our approach offers a more overall consistent picture than obtained using vacancies as the predominant point defect. In particular, we show that our approach resolves the long standing controversy regarding the contribution of point defects to the specific heat of solid $^{4}$He.Comment: 10 pages, 10 figure

CREBBP mutations in individuals without Rubinstein-Taybi syndrome phenotype

Item does not contain fulltextMutations in CREBBP cause Rubinstein-Taybi syndrome. By using exome sequencing, and by using Sanger in one patient, CREBBP mutations were detected in 11 patients who did not, or only in a very limited manner, resemble Rubinstein-Taybi syndrome. The combined facial signs typical for Rubinstein-Taybi syndrome were absent, none had broad thumbs, and three had only somewhat broad halluces. All had apparent developmental delay (being the reason for molecular analysis); five had short stature and seven had microcephaly. The facial characteristics were variable; main characteristics were short palpebral fissures, telecanthi, depressed nasal ridge, short nose, anteverted nares, short columella, and long philtrum. Six patients had autistic behavior, and two had self-injurious behavior. Other symptoms were recurrent upper airway infections (n = 5), feeding problems (n = 7) and impaired hearing (n = 7). Major malformations occurred infrequently. All patients had a de novo missense mutation in the last part of exon 30 or beginning of exon 31 of CREBBP, between base pairs 5,128 and 5,614 (codons 1,710 and 1,872). No missense or truncating mutations in this region have been described to be associated with the classical Rubinstein-Taybi syndrome phenotype. No functional studies have (yet) been performed, but we hypothesize that the mutations disturb protein-protein interactions by altering zinc finger function. We conclude that patients with missense mutations in this specific CREBBP region show a phenotype that differs substantially from that in patients with Rubinstein-Taybi syndrome, and may prove to constitute one (or more) separate entities. (c) 2016 Wiley Periodicals, Inc

Reliability of Bioelectrical Impedance Analysis for Estimating Whole‐Fish Energy Density and Percent Lipids

We evaluated bioelectrical impedance analysis (BIA) as a nonlethal means of predicting energy density and percent lipids for three fish species: Yellow perch Perca flavescens, walleye Sander vitreus, and lake whitefish Coregonus clupeaformis. Although models that combined BIA measures with fish wet mass provided strong predictions of total energy, total lipids, and total dry mass for whole fish, including BIA provided only slightly better predictions than using fish mass alone. Regression models that used BIA measures to directly predict the energy density or percent lipids of whole fish were generally better than those using body mass alone (based on Akaike’s information criterion). However, the goodness of fit of models that used BIA measures varied widely across species and at best explained only slightly more than one‐half the variation observed in fish energy density or percent lipids. Models that combined BIA measures with body mass for prediction had the strongest correlations between predicted and observed energy density or percent lipids for a validation group of fish, but there were significant biases in these predictions. For example, the models underestimated energy density and percent lipids for lipid‐rich fish and overestimated energy density and percent lipids for lipid‐poor fish. A comparison of observed versus predicted whole‐fish energy densities and percent lipids demonstrated that models that incorporated BIA measures had lower maximum percent error than models without BIA measures in them, although the errors for the BIA models were still generally high (energy density: 15‐18%; percent lipids: 82‐89%). Considerable work is still required before BIA can provide reliable predictions of whole‐fish energy density and percent lipids, including understanding how temperature, electrode placement, and the variation in lipid distribution within a fish affect BIA measures.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141722/1/tafs1519.pd