Posterior representation with a multi‐modal likelihood using the gaussian sum filter for localization in a known map

A Gaussian sum filter (GSF) with component extended Kalman filters (EKF) is proposed as an approach to localizing an autonomous vehicle in an urban environment with limited GPS availability. The GSF uses vehicle‐relative vision‐based measurements of known map features coupled with inertial navigation solutions to accomplish localization in the absence of GPS. The vision‐based measurements have multimodal measurement likelihood functions that are well represented as weighted sums of Gaussian densities. The GSF is used because of its ability to represent the posterior distribution of the vehicle pose with better efficiency (fewer terms, less computational complexity) than a corresponding bootstrap particle filter with various numbers of particles because of the interaction with measurement hypothesis tests. The expectation‐maximization algorithm is used off line to determine the representational efficiency of the particle filter in terms of an effective number of Gaussian densities. In comparison, the GSF, which uses an iterative condensation procedure after each iteration of the filter to maintain real‐time capabilities, is shown through a series of in‐depth empirical studies to more accurately maintain a representation of the posterior distribution than the particle filter using 37 min of recorded data from Cornell University's autonomous vehicle driven in an urban environment, including a 32 min GPS blackout. © 2012 Wiley Periodicals, Inc.     

Surface and subsurface products of the interaction of O2 with Ag under catalytic conditions

Polycrystalline Ag treated with O₂ at pressures up to 1 bar and at temperatures up to 920 K was examined by TDS. It was found that the peak commonly observed at 595±25 K and assigned to adsorbed atomic oxygen (O_a) is shifted to higher desorption temperatures with rising dosing temperatures. Since saturation of the uptake was not possible either, this peak was identified as dissolved atomic oxygen (O_d). The existence of a maximum for the O₂ uptake after exposure at 820 K was found. Hence, under conditions of formaldehyde synthesis ( 920 K) the ability of the catalyst to dissolve oxygen is near its maximum.     

Hedgerow species and environmental conditions effects on soil total C and N and C and N mineralization patterns of soils amended with their prunings

An important criterium in selecting species for alley cropping is themineralization pattern of their prunings. This study determined effects of 5years of hedgerow pruning applications on soil organic C and total N at threelocations in Haiti and mineralization patterns from soil amended with theprunings during an incubation using micro-lysimeters. Soils (0–5cm) under 5 hedgerows were collected at each site and analyzed fororganic C and total N. In the laboratory, ground leaves and stems (<1cm diameter) of the hedgerow species were mixed with soil at ratesof 3 and 1.5 Mg ha^–1, respectively, andaerobically incubated in the dark at 25 °C. A non-amended soilwas used as control. Soils were leached to determine mineral N at 1, 3, 7, 14,28, 42, 84 and 120 days of incubation. Evolved CO₂ was measuredfollowing each leaching procedure. At the calcareous site, application ofprunings from Leucaena leucocephala (Lam.) De Wit andDelonix regia (Boj. ex Hook. Raf.) resulted in 23 and 13%higher soil N than the control, respectively, after 5 years. There were nodifferences in total N at the other sites but soil N was highest underLeucaena hybrid and Acaciaangustissima (Mill.) Kuntze, respectively at the basaltic and highelevation sites. Soils under D. regia (calcareous) andA. angustissima and Leucaena hybrid(high elevation) had higher organic C than the respective controls. Carbon andNmineralization and C turnover were highest when soils were amended with leavesof Leucaena diversifolia (Schlecht.) Benth (calcareous andbasaltic soils) and A. angustissima (high elevation) andlowest in non-amended control soils. Stem-amended soils showed differences in Cmineralization for calcareous and high elevation soils whereas N mineralizationwas similar among treatments within sites. Carbon and N mineralization (highelevation soil) correlated positively with N concentrations of leaf prunings.Amendments with leaf prunings increased soil C and N mineralization andturnoverrates, suggesting greater nutrient availability for the crop during a shortperiod than in non-amended control soils.     

Electrophilic Aromatic Functionalization of Phenolic Photoresist Polymers

Summary Functionalization of both linear poly(4-hydroxystyrene) (PHS) and branched poly(4-hydroxystyrene) (PHS-B) was accomplished via a Reimer-Tiemann electrophilic aromatic substitution reaction. Linear and branched poly(4-hydroxystyrene-co-5-vinylsalicylaldehyde) (pHS/5VSA and pHS-B/5VSA) copolymers were observed to undergo acid-catalyzed, novolac type self-crosslinking. Both the pHS/5VSA and pHS-B/5VSA copolymer systems possessed a lower deep ultra violet microlithographic sensitivity compared to linear PHS when formulated in negative photoresists. The sluggishness of the negative photoresists containing 5-vinylsalicylaldehyde functionalized copolymers was attributed to a combination of resonance stabilization and steric hindrance effects.     

On the composition of ISO 25964 hierarchical relations (BTG,BTP, BTI)

Knowledge organization systems (KOS) can use different types of hierarchical relations: broader generic (BTG), broader partitive (BTP), and broader instantial (BTI). The latest ISO standard on thesauri (ISO 25964) has formalized these relations in a corresponding OWL ontology (De Smedt et al., ISO 25964 part 1: thesauri for information retrieval: RDF/OWL vocabulary, extension of SKOS and SKOS-XL. http://purl.org/iso25964/skos-thes, 2013) and expressed them as properties: broaderGeneric, broaderPartitive, and broaderInstantial, respectively. These relations are used in actual thesaurus data. The compositionality of these types of hierarchical relations has not been investigated systematically yet. They all contribute to the general broader (BT) thesaurus relation and its transitive generalization broader transitive defined in the SKOS model for representing KOS. But specialized relationship types cannot be arbitrarily combined to produce new statements that have the same semantic precision, leading to cases where inference of broader transitive relationships may be misleading. We define Extended properties (BTGE, BTPE, BTIE) and analyze which compositions of the original “one-step” properties and the Extended properties are appropriate. This enables providing the new properties with valuable semantics usable, e.g., for fine-grained information retrieval purposes. In addition, we relax some of the constraints assigned to the ISO properties, namely the fact that hierarchical relationships apply to SKOS concepts only. This allows us to apply them to the Getty Art and Architecture Thesaurus (AAT), where they are also used for non-concepts (facets, hierarchy names, guide terms). In this paper, we present extensive examples derived from the recent publication of AAT as linked open data.     

Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet

We propose a new semantic relation for gradable adjectives in WordNet, which enriches the present, vague, similar relation with information on the degree or intensity with which different adjectives express a shared attribute. Using lexical-semantic patterns, we mine the Web for evidence of the relative strength of adjectives like “large”, “huge” and “gigantic” with respect to their attribute (“size”). The pairwise orderings we derive allow us to construct scales on which the adjectives are located. To represent the intensity relation among gradable adjectives in WordNet, we combine ordered scales with the current WordNet dumbbells based on the relation between a pair of central adjectives and a group of undifferentiated semantically similar adjectives. A new intensity relation links the adjectives in the dumbbells and their concurrent representation on scales. Besides capturing the semantics of gradable adjectives in a way that is both intuitively clear as well as consistent with corpus data, the introduction of an intensity relation would potentially result in several specific benefits for NLP.     

A decision support system for environmental effects monitoring

The Environmental Effects Monitoring (EEM) Statistical Assessment Tool (SAT) Decision Support System (DSS) has been developed to provide a user-friendly data analysis, display and decision support tool for Canada's federal environmental effects monitoring program for the pulp and paper and mining industries. The target users include industries, consultants, regional EEM coordinators, National EEM Office and scientists involved in EEM-related research. The tool allows the assessment of the effects of effluent from industrial or other sources on fish and benthic populations. Effect endpoints, which are used as indicators of potentially important effluent effects, are measured at effluent-exposed sites and are compared statistically to measures at reference sites, in order to determine if changes have occurred and the magnitude of the changes. The main driver of the EEM-SAT DSS is its rule-based expert system. The results are used in assessing the adequacy of existing regulations for protecting aquatic environments.     

Finding the number of clusters in ordered dissimilarities

As humans, we have innate faculties that allow us to efficiently segment groups of objects. Computers, to some degree, can be programmed with similar categorical capabilities, which stem from exploratory data analysis. Out of the various subsets of data reasoning, clustering provides insight into the structure and relationships of input samples situated in a number of distributions. To determine these relationships, many clustering methods rely on one or more human inputs; the most important being the number of distributions, c, to seek. This work investigates a technique for estimating the number of clusters from a general type of data called relational data. Several numerical examples are presented to illustrate the effectiveness of the proposed method.