PhotoGeo: a photo digital library with spatial-temporal support and self-annotation

The recent popularity of digital cameras has posed a new problem: how to efficiently store and retrieve the very large number of digital photos captured and chaotically stored in multiple locations without any annotation. This paper proposes an infrastructure, called PhotoGeo, which aims at helping users with the people photo annotation, event photo annotation, storage and retrieval of personal digital photos. To achieve the desired objective, PhotoGeo uses new algorithms that make it possible to annotate photos with the key metadata to facilitate their retrieval, such as: the people who were shown in the photo (who); where it was captured (where); the date and time of capture (when); and the event that was captured. The paper concludes with a detailed evaluation of these algorithms.     

In vivo aging of gutta‐percha dental cone

Gutta‐percha cone is the most widely used material for root canal filling. The in vivo aging of this cone focus on the degradation of its main organic component, trans‐1,4‐polyisoprene, was studied. Aged cones (25 samples) from 2 to 30 years of root canal filling were extracted from different patients in the occasion of retreatment by mechanical way. The information about the aging time was given by the patients. Gel‐permeation chromatography (GPC) and infrared spectroscopy (FTIR) were the analytical techniques used. Polyisoprene degrades with time of aging, but in a slow process. Decrease in polymer molar mass from 5.7 × 10⁵ to 1.7 × 10⁵ g/mol was observed in polyisoprene from cone after 30 years of root canal filling and inside a noninfected tooth. In tooth with caries and periodontal infection, the decrease in molar mass is higher (4.6 × 10⁴ g/mol in cone with 10 years of aging). The production of carbonyl and hydroxyl groups in the aged material indicates that the process is oxidative, even in closed teeth. In these cases, the oxygen could be provided from tissue fluid. The degradation mechanism is complex and depends on many factors, besides time of root canal filling. The dental problem caused by the aging could be the production and migration of cytotoxic substances to periodontal ligament and the reduction on the canal sealing property due to the polymer weight loss. Both of them could contribute to the root canal treatment failure. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100:4082–4088, 2006     

Multi-scale stacked sequential learning

Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring labels exhibit some kind of relationship. The paper main contribution is two-fold: first, we generalize the stacked sequential learning, highlighting the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions. We tested the method on two tasks: text lines classification and image pixel classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning as well as state-of-the-art conditional random fields.     

An open source object-based framework to extract landform classes

This paper introduces a new open source, knowledge-based framework for automatic interpretation of remote sensing images, called InterIMAGE. This framework exhibits a flexible modular architecture, in which image processing operators can be associated to both root and leaf nodes of a semantic network, which accounts for a differential strategy in comparison to other object-based image analysis platforms currently available. The architecture, main features as well as an overview on the interpretation strategy implemented in InterIMAGE are presented. The paper also reports an experiment on the classification of landforms. Different geomorphometric and textural attributes obtained from ASTER/Terra images were combined with fuzzy logic to drive the interpretation semantic network. Object-based statistical agreement indices, estimated from a comparison between the classified scene and a reference map, were used to assess the classification accuracy. The InterIMAGE interpretation strategy yielded a classification result with strong agreement and proved to be effective for the extraction of landforms.     

Application of a multicriteria methodology for evaluation of energy alternatives for hydrogen production for the automotive sector – Case study

This paper presents a case study focusing on fourteen most used energy alternatives in Brazil, possible to feed large scale hydrogen production plants for the automotive sector. The evaluations are made using a Decision Making Support Method, MACBETH - Measuring Attractiveness by a Categorical Based Evaluation Technique, with the computational code M-MACBETH 3.2.0, using criteria that include economic and financial, technological, environmental and social aspects. The selected criteria that were used in the assessment, for each of the energy alternatives are capital to be invested in a plant, leveled cost of electric energy produced, CO₂ emissions, mortality rate due to the technology use and energy efficiency of technology. The main results obtained showed that photovoltaics off grid electric energy is the most attractive alternative, followed by the photovoltaic on grid alternative, for an eventual automotive hydrogen program in Brazil.     

Amino and organic acids of the prickly pear cactus (Opuntia ficus indica L.)

The amino acids of prickly pear (Opuntia ficus indica L.) proteins, free amino acids and nonvolatile organic acids were determined on fresh and lyophilised young pads. The calculated biological value of prickly pear protein was 72.6, relative to egg protein. Trace amounts of malonic, malic and citric acids in material collected at 1800 hours; traces 0.95 and 0.31 mg g^?1, respectively. In similar material analysed at 0600 hours, the concentrations of those acids were 0.36, 9.85, and 1.78 mg g^?1, respectively. Since there was a significant accumulation of the acids during the evening, crassulacean-type metabolism is suggested.     

Disinfection of Dental Instruments Contaminated with Streptococcus mutans Using Ozonated Water Alone or Combined with Ultrasound

Ozone gas diluted in water has been shown to produce significant results in terms of the elimination of microorganisms. Streptococcus mutans is the etiologic agent of dental caries. Methods using water containing ozone and an ultrasonic cleaner were employed for the disinfection of a curette. Streptococcus mutans was grown in a selective medium. The curette was submitted to disinfection by water containing ozone, by ultrasound, and then both techniques were combined. The results show that either method produced a significant microbial reduction, but the efficacy of both methods combined was greater. This method of disinfection proved to be both viable and cheap.     

Multi-agent simulator for urban segregation (MASUS): A tool to explore alternatives for promoting inclusive cities

Urban segregation represents a significant barrier to achieving social inclusion in cities. To mitigate this problem, it is necessary to implement policies founded upon a better understanding of segregation dynamics. This paper proposes MASUS, a multi-agent simulator for urban segregation, which provides a virtual laboratory for exploring the impacts of different contextual mechanisms on the emergence of segregation patterns. We illustrate the potential of MASUS through three experiments on segregation in São José dos Campos, a medium-sized city in southeast Brazil. The first experiment compares simulated outputs with empirical data, the second exemplifies the ability of MASUS to test theories, and the third tests an anti-segregation policy. We also discuss limitations of the current version of the model, and we recommend directions for further research.     

Online error correcting output codes

This article proposes a general extension of the error correcting output codes framework to the online learning scenario. As a result, the final classifier handles the addition of new classes independently of the base classifier used. In particular, this extension supports the use of both online example incremental and batch classifiers as base learners. The extension of the traditional problem independent codings one-versus-all and one-versus-one is introduced. Furthermore, two new codings are proposed, unbalanced online ECOC and a problem dependent online ECOC. This last online coding technique takes advantage of the problem data for minimizing the number of dichotomizers used in the ECOC framework while preserving a high accuracy. These techniques are validated on an online setting of 11 data sets from UCI database and applied to two real machine vision applications: traffic sign recognition and face recognition. As a result, the online ECOC techniques proposed provide a feasible and robust way for handling new classes using any base classifier.