Form inspection using kernel methods

Form inspection of non-linear surfaces is a difficult task as suitable analytical models are often unavailable. This paper presents a mathematical model for surface inspection of face-milled plates and determination of the minimum zone based on a modification of the support vector machine (SVM) technique. The SVM approach is reformulated to regression problems using a different methodology than the ‘largest margin’ paradigm. In addition, this work derives extremely simple quadratic programming (QP) problems that allow for general symbolic solutions to non-linear regression problems. The results obtained from preliminary testing allow identification of processing tendencies so that a selective sampling procedure may be applied for inspecting future plates from that lot.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Acoustic Cues for Sound Source Distance and Azimuth in Rabbits, a Racquetball and a Rigid Spherical Model

There are numerous studies measuring the transfer functions representing signal transformation between a source and each ear canal, i.e., the head-related transfer functions (HRTFs), for various species. However, only a handful of these address the effects of sound source distance on HRTFs. This is the first study of HRTFs in the rabbit where the emphasis is on the effects of sound source distance and azimuth on HRTFs. With the rabbit placed in an anechoic chamber, we made acoustic measurements with miniature microphones placed deep in each ear canal to a sound source at different positions (10–160 cm distance, ±150° azimuth). The sound was a logarithmically swept broadband chirp. For comparisons, we also obtained the HRTFs from a racquetball and a computational model for a rigid sphere. We found that (1) the spectral shape of the HRTF in each ear changed with sound source location; (2) interaural level difference (ILD) increased with decreasing distance and with increasing frequency. Furthermore, ILDs can be substantial even at low frequencies when distance is close; and (3) interaural time difference (ITD) decreased with decreasing distance and generally increased with decreasing frequency. The observations in the rabbit were reproduced, in general, by those in the racquetball, albeit greater in magnitude in the rabbit. In the sphere model, the results were partly similar and partly different than those in the racquetball and the rabbit. These findings refute the common notions that ILD is negligible at low frequencies and that ITD is constant across frequency. These misconceptions became evident when distance-dependent changes were examined

Spectrum Labeling: Theory and Practice

In recent years, a number of instruments have been developed for continuous, real-time monitoring of the environment. Aerosol mass spectrometers can analyze several hundred atmospheric aerosol particles per minute and generate a plot of mass-to-charge versus intensity (a mass spectrum) for each particle. The mass spectrum could be used to identify the compounds present in the particle in realtime, in contrast to conventional filter-based approaches in which filters collect samples over a period of time and are then analyzed in a laboratory, but our ability to analyze the data is currently a bottle-neck. In this paper, we introduce the problem of labeling a particle’s mass spectrum with the substances it contains, and develop several formal representations of the problem, taking into account practical complications such as unknowns and noise. Our contributions include the introduction and formalization of a novel data mining problem, theoretical characterizations of the central difficulty underlying the problem, algorithms for solving the problem, metrics to measure the quality of labeling, experimental evaluation of the effectiveness of these algorithms, and comparisons with alternative machine learning techniques (showing that our algorithms, although slower, achieve uniformly superior accuracy without the need for training datasets!). 1