On Stochastic Subgradient Mirror-Descent Algorithm with Weighted Averaging

This paper considers stochastic subgradient mirror-descent method for solving constrained convex minimization problems. In particular, a stochastic subgradient mirror-descent method with weighted iterate-averaging is investigated and its per-iterate convergence rate is analyzed. The novel part of the approach is in the choice of weights that are used to construct the averages. Through the use of these weighted averages, we show that the known optimal rates can be obtained with simpler algorithms than those currently existing in the literature. Specifically, by suitably choosing the stepsize values, one can obtain the rate of the order $1/k$ for strongly convex functions, and the rate $1/\sqrt{k}$ for general convex functions (not necessarily differentiable). Furthermore, for the latter case, it is shown that a stochastic subgradient mirror-descent with iterate averaging converges (along a subsequence) to an optimal solution, almost surely, even with the stepsize of the form $1/\sqrt{1+k}$, which was not previously known. The stepsize choices that achieve the best rates are those proposed by Paul Tseng for acceleration of proximal gradient methods

Search and Non-Wage Job Characteristics

This paper quantifies the importance of non-wage job characteristics to workers by estimating a structural on-the-job search model. The model generalizes the standard search framework by allowing workers to search for jobs based on both wages and job-specific non-wage utility flows. Within the structure of the search model, data on accepted wages and wage changes at job transitions identify the importance of non-wage utility through revealed preference. The parameters of the model are estimated by simulated minimum distance using the 1997 cohort of the National Longitudinal Survey of Youth (NLSY97). The estimates reveal that utility from non-wage job characteristics plays an important role in determining job mobility, the value of jobs to workers, and the gains from job search. More specifically, non-wage utility accounts for approximately one-third of the total gains from job mobility. These large non-pecuniary gains from search are missed by search models which assume that the wage captures the entire value of a job to a worker.job search, non-wage job characteristics, wage growth, revealed preference, compensating differentials

Bounds on the Hilbert-Kunz Multiplicity

In this paper we give new lower bounds on the Hilbert-Kunz multiplicity of unmixed non-regular local rings, bounding them uniformly away from one. Our results improve previous work of Aberbach and Enescu.Comment: Some minor typos fixed, especially Theorem 3.7 (min instead of max). Corollary 2.4 is added by the referee's suggestio

Water and oil signal assignment in low-moisture mozzarella as determined by time-domain NMR T2 relaxometry

A time-domain H-1 nuclear magnetic resonance relaxometry method was elaborated for the rapid microstructural characterization of mozzarella cheese. For this purpose, there is a strong need to know how the experimentally determined T-2 relaxation time distribution can be related to specific constituents in mozzarella. In this study, a detailed investigation is offered for fresh and aged low-moisture mozzarella cheese, often applied as a pizza cheese, by application of both a conventional Carr-Purcell-Meiboom-Gill (CPMG) sequence and a free-induction decay CPMG (FID-CPMG) sequence. The relaxation behavior was further elucidated by addition of deuterium oxide and by mild heat treatment of samples. The relaxation times of water protons in mozzarella were found to range from a few microseconds to some tens of milliseconds (in aged mozzarella) or to about hundred milliseconds (in fresh mozzarella). The upper limit of the T-2 distribution can even be extended to the seconds range upon releasing water protons from the mozzarella matrix using a mild heat treatment or upon addition of deuterated water. Both stimuli also provided evidence for the absorption of water into the cheese matrix. The potential release and uptake of water demonstrated that mozzarella acts as a very dynamic system during production and storage. The detected differences in the behavior of the water fraction between fresh and aged low-moisture mozzarella might be utilized to study the influence of either production and/or storage conditions on the cheese ripening process

Risk Perceptions of Arsenic in Tap Water and Consumption of Bottled Water

The demand for bottled water has increased rapidly over the past decade, but bottled water is extremely costly compared to tap water. The convenience of bottled water surely matters to consumers, but are others factors at work? This manuscript examines whether purchases of bottled water are associated with the perceived risk of tap water. All of the past studies on bottled water consumption have used simple scale measures of perceived risk that do not correspond to risk measures used by risk analysts. We elicit a probability-based measure of risk and find that as perceived risks rise, expenditures for bottled water rise.Environmental Economics and Policy, Risk and Uncertainty, Q25, Q53, I12,

Surface-type classification using RGB-D

This paper proposes an approach to improve surface-type classification of images containing inconsistently illuminated surfaces. When a mobile inspection robot is visually inspecting surface-types in a dark environment and a directional light source is used to illuminate the surfaces, the images captured may exhibit illumination variance that can be caused by the orientation and distance of the light source relative to the surfaces. In order to accurately classify the surface-types in these images, either the training image dataset needs to completely incorporate the illumination variance or a way to extract color features that can provide high classification accuracy needs to be identified. In this paper diffused reflectance values are extracted as new color features to classifying surface-types. In this approach, Red, Green, Blue-Depth (RGB-D) data is collected from the environment, and a reflectance model is used to calculate a diffused reflectance value for a pixel in each Red, Green, Blue (RGB) color channel. The diffused reflectance values can be used to train a multiclass support vector machine classifier to classify surface-types. Experiments are conducted in a mock bridge maintenance environment using a portable RGB-Depth sensor package with an attached light source to collect surface-type data. The performance of a classifier trained with diffused reflectance values is compared against classifiers trained with other color features including RGB and Lcolor spaces. Results show that the classifier trained with the diffused reflectance values can achieve consistently higher classification accuracy than the classifiers trained with RGB and Lab features. For test images containing a single surface plane, diffused reflectance values consistently provide greater than 90% classification accuracy; and for test images containing a complex scene with multiple surface-types and surface planes, diffused reflectance values are shown to provide an increase in overall accuracy over RGB and Lab by 49.24% and 13.66%, respectively. © 2013 IEEE

Image segmentation for surface material-type classification using 3D geometry information

This paper describes a novel approach for the segmentation of complex images to determine candidates for accurate material-type classification. The proposed approach identifies classification candidates based on image quality calculated from viewing distance and angle information. The required viewing distance and angle information is extracted from 3D fused images constructed from laser range data and image data. This approach sees application in material-type classification of images captured with varying degrees of image quality attributed to geometric uncertainty of the environment typical for autonomous robotic exploration. The proposed segmentation approach is demonstrated on an autonomous bridge maintenance system and validated using gray level co-occurrence matrix (GLCM) features combined with a naive Bayes classifier. Experimental results demonstrate the effects of viewing distance and angle on classification accuracy and the benefits of segmenting images using 3D geometry information to identify candidates for accurate material-type classification. ©2010 IEEE

Asteroid (3200) Phaethon: colors, phase curve, limits on cometary activity and fragmentation

We report on a multi-observatory campaign to examine asteroid 3200 Phaethon during its December 2017 close approach to Earth, in order to improve our measurements of its fundamental parameters, and to search for surface variations, cometary activity and fragmentation. The mean colors of Phaethon are B-V = 0.702 +/- 0.004, V-R = 0.309 +/- 0.003, R-I = 0.266 +/- 0.004, neutral to slightly blue, consistent with previous classifications of Phaethon as a F-type or B-type asteroid. Variations in Phaethon's B-V colors (but not V-R or R-I) with observer sub-latitude are seen and may be associated with craters observed by the Arecibo radar. High cadence photometry over phases from 20 to 100 degrees allows a fit to the values of the HG photometric parameters; H = 14.57 +/- 0.02, 13.63 +/- 0.02, 13.28 +/- 0.02, 13.07 +/- 0.02; G = 0.00 +/- 0.01, -0.09 +/- 0.01, -0.10 +/- 0.01, -0.08 +/- 0.01 in the BVRI filters respectively; the negative G values are consistent with other observations of F type asteroids. Light curve variations were seen that are also consistent with concavities reported by Arecibo, indicative of large craters on Phaethon's surface whose ejecta may be the source of the Geminid meteoroid stream. A search for gas/dust production set an upper limit of 0.06 +/- 0.02 kg/s when Phaethon was 1.449 AU from the Sun, and 0.2 +/- 0.1 kg/s at 1.067 AU. A search for meter-class fragments accompanying Phaethon did not find any whose on-sky motion was not also consistent with background main belt asteroids.Comment: Accepted by the Astronomical Journal, 15 pages, 8 figures, 1 animated figur