SenseCam image localisation using hierarchical SURF trees

The SenseCam is a wearable camera that automatically takes photos of the wearer's activities, generating thousands of images per day. Automatically organising these images for efficient search and retrieval is a challenging task, but can be simplified by providing semantic information with each photo, such as the wearer's location during capture time. We propose a method for automatically determining the wearer's location using an annotated image database, described using SURF interest point descriptors. We show that SURF out-performs SIFT in matching SenseCam images and that matching can be done efficiently using hierarchical trees of SURF descriptors. Additionally, by re-ranking the top images using bi-directional SURF matches, location matching performance is improved further

Towards learning free naive bayes nearest neighbor-based domain adaptation

As of today, object categorization algorithms are not able to achieve the level of robustness and generality necessary to work reliably in the real world. Even the most powerful convolutional neural network we can train fails to perform satisfactorily when trained and tested on data from different databases. This issue, known as domain adaptation and/or dataset bias in the literature, is due to a distribution mismatch between data collections. Methods addressing it go from max-margin classifiers to learning how to modify the features and obtain a more robust representation. Recent work showed that by casting the problem into the image-to-class recognition framework, the domain adaptation problem is significantly alleviated [23]. Here we follow this approach, and show how a very simple, learning free Naive Bayes Nearest Neighbor (NBNN)-based domain adaptation algorithm can significantly alleviate the distribution mismatch among source and target data, especially when the number of classes and the number of sources grow. Experiments on standard benchmarks used in the literature show that our approach (a) is competitive with the current state of the art on small scale problems, and (b) achieves the current state of the art as the number of classes and sources grows, with minimal computational requirements. © Springer International Publishing Switzerland 2015

Superconductivity and magnetic order in the non-centrosymmetric Half Heusler compound ErPdBi

We report superconductivity at $T_c = 1.22$ K and magnetic order at $T_N = 1.06$ K in the semi-metallic noncentrosymmetric Half Heusler compound ErPdBi. The upper critical field, $B_{c2}$, has an unusual quasi-linear temperature variation and reaches a value of 1.6 T for $T \rightarrow 0$. Magnetic order is found below $T_c$ and is suppressed at $B{_M} \sim 2.5$ T for $T \rightarrow 0$. Since $T_c \simeq T_N$, the interaction of superconductivity and magnetism is expected to give rise to a complex ground state. Moreover, electronic structure calculations show ErPdBi has a topologically nontrivial band inversion and thus may serve as a new platform to study the interplay of topological states, superconductivity and magnetic order.Comment: 6 pages, 5 figures; accepted for publication in Europhysics Letter

ClassCut for Unsupervised Class Segmentation

Abstract. We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model. The method is based on a segmentation energy defined over all images at the same time, which can be optimized efficiently by techniques used before in interactive segmentation. Over iterations, our method progressively learns a class model by integrating observations over all images. In addition to appearance, this model captures the location and shape of the class with respect to an automatically determined coordinate frame common across images. This frame allows us to build stronger shape and location models, similar to those used in object class detection. Our method is inspired by interactive segmentation methods [1], but it is fully automatic and learns models characteristic for the object class rather than specific to one particular object/image. We experimentally demonstrate on the Caltech4, Caltech101, and Weizmann horses datasets that our method (a) transfers class knowledge across images and this improves results compared to segmenting every image independently; (b) outperforms Grabcut [1] for the task of unsupervised segmentation; (c) offers competitive performance compared to the state-of-the-art in unsupervised segmentation and in particular it outperforms the topic model [2].

Hubungan Dukungan Keluarga dengan Kualitas Hidup Pasien Gagal Ginjal Kronik yang Menjalani Terapi Hemodialisis di RSUD Arifin Achmad Pekanbaru

The purpose of study was to identify the correlation between the family support and quality of life of patients with chronic renal failure undergoing hemodialysis therapy at Arifin Achmad general hospital Pekanbaru. This study was description correlation with cross sectional approach. Sampling technique in this study was total sampling with 105 respondents. Instruments used were questionnaires which were tested the validity and reliability. Data analysis used univariate and bivariate analysis. The result showed that pvalue = 0.002, it could be concluded that there was a relationship between family support and quality of life of CRF patients undergoing hemodialysis therapy at Arifin Achmad general hospital Pekanbaru. Families who have family member undergoing hemodialysis therapy are expected to always give both moral and material support, so that the quality of life of patients undergoing hemodialysis CRF can be maintained

Om Mund- og Klovesygen samt Midler mod Udbredelsen af smitsomme Sygdomme.

Om Mund- og Klovesygen samt Midler mod Udbredelsen af smitsomme Sygdomme

UV Degradation of the Optical Properties of Acrylic for Neutrino and Dark Matter Experiments

UV-transmitting (UVT) acrylic is a commonly used light-propagating material in neutrino and dark matter detectors as it has low intrinsic radioactivity and exhibits low absorption in the detectors' light producing regions, from 350 nm to 500 nm. Degradation of optical transmittance in this region lowers light yields in the detector, which can affect energy reconstruction, resolution, and experimental sensitivities. We examine transmittance loss as a result of short- and long-term UV exposure for a variety of UVT acrylic samples from a number of acrylic manufacturers. Significant degradation peaking at 343 nm was observed in some UVT acrylics with as little as three hours of direct sunlight, while others exhibited softer degradation peaking at 310 nm over many days of exposure to sunlight. Based on their measured degradation results, safe time limits for indoor and outdoor UV exposure of UVT acrylic are formulated.Comment: 13 pages, 6 figures, 3 tables; To be submitted to Journal of Instrumentatio

Fluxes of microbes, organic aerosols, dust, sea-salt Na ions, non-sea-salt Ca ions, and methanesulfonate onto Greenland and Antarctic ice

Using a spectrofluorimeter with 224-nm laser excitation and six emission bands from 300 to 420 nm to measure fluorescence intensities at 0.3-mm depth intervals in ice cores, we report results of the first comparative study of concentrations of microbial cells (using the spectrum of protein-bound tryptophan (Trp) as a proxy) and of aerosols with autofluorescence spectra different from Trp (denoted "non-Trp") as a function of depth in ice cores from West Antarctica (WAIS Divide and Siple Dome) and Greenland (GISP2). The ratio of fluxes of microbial cells onto West Antarctic (WAIS Divide) versus Greenland sites is 0.13±0.06; the ratio of non-Trp aerosols onto WAIS Divide versus Greenland sites is 0.16±0.08; and the ratio of non-sea-salt Ca<sup>2+</sup> ions (a proxy for dust grains) onto WAIS Divide versus Greenland sites is 0.06±0.03. All of these are roughly comparable to the ratio of fluxes of dust onto Antarctic versus Greenland sites (0.08±0.05). By contrast to those values, which are considerably lower than unity, the ratio of fluxes of methanesulfonate (MSA) onto Antarctic versus Greenland sites is 1.9±0.4 and the ratio of sea-salt Na<sup>2+</sup> ions onto WAIS Divide versus Greenland sites is 3.0±2. These ratios are more than an order of magnitude higher than those in the first grouping. We infer that the correlation of microbes and non-Trp aerosols with non-sea-salt Ca and dust suggests a largely terrestrial rather than marine origin. The lower fluxes of microbes, non-Trp aerosols, non-sea-salt Ca and dust onto WAIS Divide ice than onto Greenland ice may be due to the smaller areas of their source regions and less favorable wind patterns for transport onto Antarctic ice than onto Greenland ice. The correlated higher relative fluxes of MSA and marine Na onto Antarctic versus Greenland ice is consistent with the view that both originate largely on or around sea ice, with the Antarctic sea ice being far more extensive than that around Greenland