Measuring and Predicting Importance of Objects in Our Visual World

Associating keywords with images automatically is an approachable and useful goal for visual recognition researchers. Keywords are distinctive and informative objects. We argue that keywords need to be sorted by 'importance', which we define as the probability of being mentioned first by an observer. We propose a method for measuring the `importance' of words using the object labels that multiple human observers give an everyday scene photograph. We model object naming as drawing balls from an urn, and fit this model to estimate `importance'; this combines order and frequency, enabling precise prediction under limited human labeling. We explore the relationship between the importance of an object in a particular image and the area, centrality, and saliency of the corresponding image patches. Furthermore, our data shows that many words are associated with even simple environments, and that few frequently appearing objects are shared across environments

Experiments with phase transitions at very high pressure

Diamond cells were constructed for use to 1 Mbar. A refrigerator for cooling diamond cells was adapted for studies between 15 and 300 K. A cryostat for superconductivity studies between 1.5 to 300 K was constructed. Optical equipment was constructed for fluorescence, transmission, and reflectance studies. X-ray equipment was adapted for use with diamond cells. Experimental techniques were developed for X-ray diffraction studies using synchrotron radiation. AC susceptibility techniques were developed for detecting superconducting transitions. The following materials were studied: compressed solidified gases (Xe, Ar), semiconductors (Ge, Si, GaAs), superconductors (Nb3Ge, Nb3Si, Nb3As, CuCl), molecular crystals (I)

Application of a system modification technique to dynamic tuning of a spinning rotor blade

An important consideration in the development of modern helicopters is the vibratory response of the main rotor blade. One way to minimize vibration levels is to ensure that natural frequencies of the spinning main rotor blade are well removed from integer multiples of the rotor speed. A technique for dynamically tuning a finite-element model of a rotor blade to accomplish that end is demonstrated. A brief overview is given of the general purpose finite element system known as Engineering Analysis Language (EAL) which was used in this work. A description of the EAL System Modification (SM) processor is then given along with an explanation of special algorithms developed to be used in conjunction with SM. Finally, this technique is demonstrated by dynamically tuning a model of an advanced composite rotor blade

Objects predict fixations better than early saliency

Humans move their eyes while looking at scenes and pictures. Eye movements correlate with shifts in attention and are thought to be a consequence of optimal resource allocation for high-level tasks such as visual recognition. Models of attention, such as “saliency maps,” are often built on the assumption that “early” features (color, contrast, orientation, motion, and so forth) drive attention directly. We explore an alternative hypothesis: Observers attend to “interesting” objects. To test this hypothesis, we measure the eye position of human observers while they inspect photographs of common natural scenes. Our observers perform different tasks: artistic evaluation, analysis of content, and search. Immediately after each presentation, our observers are asked to name objects they saw. Weighted with recall frequency, these objects predict fixations in individual images better than early saliency, irrespective of task. Also, saliency combined with object positions predicts which objects are frequently named. This suggests that early saliency has only an indirect effect on attention, acting through recognized objects. Consequently, rather than treating attention as mere preprocessing step for object recognition, models of both need to be integrated

The complex networks of earth minerals and chemical elements

We study the large-scale organization of the mineral-mineral (MMN) and element-element (EEN) complex networks by analyzing their topological structures. We see that the MMN and EEN are homogeneous, display large cliquishness, small average path length and large average degrees. Most of these networks display uniform degree distribution with the exception of the weighted EEN, which display a power-law degree distribution with exponential tail. All these topological characteristics appear to be consequence of the evolutionary mechanisms giving place to the minerals on Earth mantle, which as a whole display a relatively uniform major element composition. We also study the correlations between some topological network parameters and the abundance of chemical elements in different scenarios. Good correlation is obtained between the weighted degree and the abundance of elements in Earth's crustal rocks

Magnetometer uses bismuth-selenide

Characteristics of bismuth-selenide magnetometer are described. Advantages of bismuth-selenide magnetometer over standard magnetometers are stressed. Thermal stability of bismuth-selenide magnetometer is analyzed. Linearity of output versus magnetic field over wide range of temperatures is reported

How the parts organize in the whole : a top-downview of molecular descriptors and properties for QSARand drug design

Sometimes the complexity of a system, or the properties derived from it, do depend neither on the individual characteristics of the components of the system nor on the nature of the physical forces that hold them together. In such cases the properties derived from the 'organization' of the system given by the connectivity of its elements can be determinant for explaining the structure of such systems. Here we explore the necessity of accounting for these structural characteristics in the molecular descriptors. We show that graph theory is the most appropriate mathematical theory to account for such molecular features. We review a method (TOPS-MODE) that is able to transform simple molecular descriptors, such as logP, polar surface area, molar refraction, charges, etc., into series of descriptors that account for the distribution of these characteristics (hydrophobicity, polarity, steric effects, etc) across the molecule. We explain the mathematical and physical principles of the TOPS-MODE method and develop three examples covering the description and interpretation of skin sensitisation of chemicals, chromosome aberration produced by organic molecules and drug binding to human serum albumin