Multi-sensor Simultaneous Localization and Mapping

Simultaneous localization and mapping(SLAM) is a very important problem in mobile robotics. Many solutions have been proposed by different scientists during the last two decades, nevertheless few studies have considered the use of multiple sensors simultane¬ously. The solution is on combining several data sources with the aid of an Extended Kalman Filter (EKF). Two approaches are proposed. The first one is to use the ordinary EKF SLAM algorithm for each data source separately in parallel and then at the end of each step, fuse the results into one solution. Another proposed approach is the use of multiple data sources simultaneously in a single filter. The comparison of the computational com¬plexity of the two methods is also presented. The first method is almost four times faster than the second one.

Efficient image mosaicing for multi-robot visual underwater mapping

Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

A systematic mapping study of web services discovery mechanisms

Context: Web services have been gaining popularity due to the success of service oriented architecture and cloud computing. Web services offer tremendous opportunity for service developers to publish their services and applications over the boundaries of the organization or company. However, to fully exploit these opportunities it is necessary to find efficient discovery mechanism thus, Web services discovering mechanism has attracted a considerable attention in Semantic Web research, however, there have been no literature surveys that systematically map the present research result thus overall impact of these research efforts and level of maturity of their results are still unclear. This thesis aims at providing an overview of the current state of research into Web services discovering mechanism using systematic mapping. The work is based on the papers published 2004 to 2013, and attempts to elaborate various aspects of the analyzed literature including classifying them in terms of the architecture, frameworks and methods used for web services discovery mechanism. Objective: The objective if this work is to summarize the current knowledge that is available as regards to Web service discovery mechanisms as well as to systematically identify and analyze the current published research works in order to identify different approaches presented. Method: A systematic mapping study has been employed to assess the various Web Services discovery approaches presented in the literature. Systematic mapping studies are useful for categorizing and summarizing the level of maturity research area. Results: The result indicates that there are numerous approaches that are consistently being researched and published in this field. In terms of where these researches are published, conferences are major contributing publishing arena as 48% of the selected papers were conference published papers illustrating the level of maturity of the research topic. Additionally selected 52 papers are categorized into two broad segments namely functional and non-functional based approaches taking into consideration architectural aspects and information retrieval approaches, semantic matching, syntactic matching, behavior based matching as well as QOS and other constraints.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Recombinant antigen-based immuno-slot blot method for serodiagnosis of syphilis

Three recombinant antigens of Treponema pallidum Nichols strain were fused with GST, cloned and expressed in Escherichia coli, resulting in high levels of GST-rTp47 and GST-rTp17 expression, and supplementation with arginine tRNA for the AGR codon was needed to obtain GST-rTp15 overexpression. Purified fusion protein yields were 1.9, 1.7 and 5.3 mg/l of cell culture for GST-rTp47, GST-rTp17 and GST-rTp15, respectively. The identities of the antigens obtained were confirmed by automated DNA sequencing using ABI Prism 310 and peptide mapping by Finningan LC/MS. These recombinant antigens were evaluated by immuno-slot blot techniques applied to 137 serum samples from patients with a clinical and laboratory diagnosis of syphilis (61 samples), from healthy blood donors (50 samples), individuals with sexually transmitted disease other than syphilis (3 samples), and from individuals with other spirochetal diseases such as Lyme disease (20 samples) and leptospirosis (3 samples). The assay had sensitivity of 95.1% (95% CI, 86.1 to 98.7%) and a specificity of 94.7% (95% CI, 87.0 to 98.7%); a stronger reactivity was observed with fraction rTp17. The immunoreactivity results showed that fusion recombinant antigens based-immuno-slot blot techniques are suitable for use in diagnostic assays for syphilis.

A systematic mapping study on open data

This thesis presented the overview of Open Data research area, quantity of evidence and establishes the research evidence based on the Systematic Mapping Study (SMS). There are 621 such publications were identified published between years 2005 and 2014, but only 243 were selected in the review process. This thesis highlights the implications of Open Data principals’ proliferation in the emerging era of the accessibility, reusability and sustainability of data transparency. The findings of mapping study are described in quantitative and qualitative measurement based on the organization affiliation, countries, year of publications, research method, star rating and units of analysis identified. Furthermore, units of analysis were categorized by development lifecycle, linked open data, type of data, technical platforms, organizations, ontology and semantic, adoption and awareness, intermediaries, security and privacy and supply of data which are important component to provide a quality open data applications and services. The results of the mapping study help the organizations (such as academia, government and industries), re-searchers and software developers to understand the existing trend of open data, latest research development and the demand of future research. In addition, the proposed conceptual framework of Open Data research can be adopted and expanded to strengthen and improved current open data applications.

A study of chymotrypsin immobilization conditions for improved peptide mapping

La cartographie peptidique est une technique de grande importance utilisée lors de l’identification des protéines et la caractérisation des modifications post-traductionnelles des protéines. Deux méthodes sont utilisées afin de couper les protéines en peptides pour la cartographie : les méthodes chimiques et les méthodes enzymatiques. Dans ce projet, l’enzyme chymotrypsine a été utilisée pour l’hydrolyse (la digestion) des liens peptidiques. Cependant, l’autoprotéolyse des enzymes peut augmenter la complexité des échantillons, rendant ainsi ardue l’obtention de pics résolus suite à l’apparition de pics non-désirés dans la carte peptidique. Par conséquent, nous avons utilisé la réticulation des enzymes protéolytiques par réaction avec le glutaraldéhyde (GA) donnant une enzyme insoluble afin de réduire l’autoprotéolyse. L’immobilisation de la chymotrypsine par GA a été effectuée selon une méthode rapportée précédemment par le groupe Waldron. L’électrophorèse capillaire (CE) couplée à l’absorption UV-visible a été utilisée pour la séparation et la détection de peptides et pour obtenir ainsi une cartographie peptidique. Deux tampons différents ont été évalués afin d’obtenir les meilleures conditions pour la digestion de substrats protéiques par la chymotrypsine libre (soluble) ou la GAchymotrypsine et l’analyse par CE. Les cartes des peptides autoprotéolytiques ont été comparées entre les deux formats de chymotrypsine. Afin d’améliorer la cartographie peptidique, nous avons évalué trois méthodes de conditionnement du capillaire CE et deux méthodes pour stopper la digestion. Le bicarbonate d’ammonium s’est avéré être le tampon optimal pour la digestion en solution et l’utilisation d’un bain d’acétone et de glace sèche s’est avérée être la méthode optimale pour stopper la digestion. Une solution de SDS, 25 mM, dans l’étape de rinçage a été utilisée après chaque analyse CE et a permis d’améliorer la résolution des cartes peptidiques. La comparaison entre l’autoprotéolyse de la chymotrypsine libre et de celle immobilisé par GA a été effectuée par des tests utilisant une gamme de six différentes combinaisons de conditions afin d’évaluer le temps (30 et 240 min) et la température de digestion (4, 24 et 37°C). Dans ces conditions, nos résultats ont confirmé que le GA-chymotrypsine réduit l’autoprotéolyse par rapport à l’enzyme libre. La digestion (à 37°C/240 min) de deux substrats modèles par la chymotrypsine libre et immobilisée en fonction de la température de dénaturation du substrat a été étudiée. iii Avant la digestion, les substrats (l’albumine de sérum bovine, BSA, et la myoglobine) ont été dénaturés par chauffage pendant 45 min à trois températures différentes (60, 75 et 90°C). Les résultats ont démontré que la dénaturation par chauffage du BSA et de la myoglobine n’a pas amélioré la cartographie peptidique pour la GA-chymotrypsine, tandis que la digestion de ceux-ci en présence de la chymotrypsine libre a amélioré de façon quantifiable à des températures élevées. Ainsi, le chauffage du substrat à 90°C avec l’enzyme soluble facilite le dépliement partiel du substrat et sa digestion limitée, ce qui a été mieux pour la myoglobine que pour la BSA.

Characterization of glutaraldehyde-immobilized chymotrypsin and an in-situ immobilized enzyme reactor using capillary electrophoresis-based peptide mapping

La digestion enzymatique des protéines est une méthode de base pour les études protéomiques ainsi que pour le séquençage en mode « bottom-up ». Les enzymes sont ajoutées soit en solution (phase homogène), soit directement sur le gel polyacrylamide selon la méthode déjà utilisée pour l’isolation de la protéine. Les enzymes protéolytiques immobilisées, c’est-à-dire insolubles, offrent plusieurs avantages tels que la réutilisation de l’enzyme, un rapport élevé d’enzyme-sur-substrat, et une intégration facile avec les systèmes fluidiques. Dans cette étude, la chymotrypsine (CT) a été immobilisée par réticulation avec le glutaraldehyde (GA), ce qui crée des particules insolubles. L’efficacité d’immobilisation, déterminée par spectrophotométrie d’absorbance, était de 96% de la masse totale de la CT ajouté. Plusieurs différentes conditions d’immobilisation (i.e., réticulation) tels que la composition/pH du tampon et la masse de CT durant la réticulation ainsi que les différentes conditions d’entreposage tels que la température, durée et humidité pour les particules GA-CT ont été évaluées par comparaison des cartes peptidiques en électrophorèse capillaire (CE) des protéines standards digérées par les particules. Les particules de GA-CT ont été utilisés pour digérer la BSA comme exemple d’une protéine repliée large qui requit une dénaturation préalable à la digestion, et pour digérer la caséine marquée avec de l’isothiocyanate de fluorescéine (FITC) comme exemple d’un substrat dérivé afin de vérifier l’activité enzymatique du GA-CT dans la présence des groupements fluorescents liés au substrat. La cartographie peptidique des digestions par les particules GA-CT a été réalisée par CE avec la détection par absorbance ultraviolet (UV) ou fluorescence induite par laser. La caséine-FITC a été, en effet, digérée par GA-CT au même degré que par la CT libre (i.e., soluble). Un microréacteur enzymatique (IMER) a été fabriqué par immobilisation de la CT dans un capillaire de silice fondu du diamètre interne de 250 µm prétraité avec du 3-aminopropyltriéthoxysilane afin de fonctionnaliser la paroi interne avec les groupements amines. Le GA a été réagit avec les groupements amine puis la CT a été immobilisée par réticulation avec le GA. Les IMERs à base de GA-CT étaient préparé à l’aide d’un système CE automatisé puis utilisé pour digérer la BSA, la myoglobine, un peptide ayant 9 résidus et un dipeptide comme exemples des substrats ayant taille large, moyenne et petite, respectivement. La comparaison des cartes peptidiques des digestats obtenues par CE-UV ou CE-spectrométrie de masse nous permettent d’étudier les conditions d’immobilisation en fonction de la composition et le pH du tampon et le temps de réaction de la réticulation. Une étude par microscopie de fluorescence, un outil utilisé pour examiner l’étendue et les endroits d’immobilisation GA-CT dans l’IMER, ont montré que l’immobilisation a eu lieu majoritairement sur la paroi et que la réticulation ne s’est étendue pas si loin au centre du capillaire qu’anticipée.

A Variational Calculation of TE and TM Cutoff Wavenumbers in Circular Eccentric Guides by Conformal Mapping

The cutoff wavenumbers of higher order modes in circular eccentric guides are computed with the variational analysis combined with a conformal mapping. A conformal mapping is applied to the variational formulation, and the variational equation is solved by the finite-element method. Numerical results for TE and TM cutoff wavenumbers are presented for different distances between the centers and ratio of the radii. Comparisons with numerical results found in the literature validate the presented method

Genetic algorithm based indicator sequence method for exon prediction

Considerable research effort has been devoted in predicting the exon regions of genes. The binary indicator (BI), Electron ion interaction pseudo potential (EIIP), Filter method are some of the methods. All these methods make use of the period three behavior of the exon region. Even though the method suggested in this paper is similar to above mentioned methods , it introduces a set of sequences for mapping the nucleotides selected by applying genetic algorithm and found to be more promising

Value Stream Analysis and Mapping for Product Development

This paper explores the concept of Value Stream Analysis and Mapping (VSA/M) as applied to Product Development (PD) efforts. Value Stream Analysis and Mapping is a method of business process improvement. The application of VSA/M began in the manufacturing community. PD efforts provide a different setting for the use of VSA/M. Site visits were made to nine major U.S. aerospace organizations. Interviews, discussions, and participatory events were used to gather data on (1) the sophistication of the tools used in PD process improvement efforts, (2) the lean context of the use of the tools, and (3) success of the efforts. It was found that all three factors were strongly correlated, suggesting success depends on both good tools and lean context. Finally, a general VSA/M method for PD activities is proposed. The method uses modified process mapping tools to analyze and improve process.

Value Stream Analysis and Mapping for Product Development

This paper explores the concept of Value Stream Analysis and Mapping (VSA/M) as applied to Product Development (PD) efforts. Value Stream Analysis and Mapping is a method of business process improvement. The application of VSA/M began in the manufacturing community. PD efforts provide a different setting for the use of VSA/M. Site visits were made to nine major U.S. aerospace organizations. Interviews, discussions, and participatory events were used to gather data on (1) the sophistication of the tools used in PD process improvement efforts, (2) the lean context of the use of the tools, and (3) success of the efforts. It was found that all three factors were strongly correlated, suggesting success depends on both good tools and lean context. Finally, a general VSA/M method for PD activities is proposed. The method uses modified process mapping tools to analyze and improve process.

An alternative method for dating unknown tephras based on a segmented regression model

In CoDaWork’05, we presented an application of discriminant function analysis (DFA) to 4 different compositional datasets and modelled the first canonical variable using a segmented regression model solely based on an observation about the scatter plots. In this paper, multiple linear regressions are applied to different datasets to confirm the validity of our proposed model. In addition to dating the unknown tephras by calibration as discussed previously, another method of mapping the unknown tephras into samples of the reference set or missing samples in between consecutive reference samples is proposed. The application of these methodologies is demonstrated with both simulated and real datasets. This new proposed methodology provides an alternative, more acceptable approach for geologists as their focus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age of unknown tephra. Kew words: Tephrochronology; Segmented regression

Efficient topology estimation for large scale optical mapping

Large scale image mosaicing methods are in great demand among scientists who study different aspects of the seabed, and have been fostered by impressive advances in the capabilities of underwater robots in gathering optical data from the seafloor. Cost and weight constraints mean that lowcost Remotely operated vehicles (ROVs) usually have a very limited number of sensors. When a low-cost robot carries out a seafloor survey using a down-looking camera, it usually follows a predetermined trajectory that provides several non time-consecutive overlapping image pairs. Finding these pairs (a process known as topology estimation) is indispensable to obtaining globally consistent mosaics and accurate trajectory estimates, which are necessary for a global view of the surveyed area, especially when optical sensors are the only data source. This thesis presents a set of consistent methods aimed at creating large area image mosaics from optical data obtained during surveys with low-cost underwater vehicles. First, a global alignment method developed within a Feature-based image mosaicing (FIM) framework, where nonlinear minimisation is substituted by two linear steps, is discussed. Then, a simple four-point mosaic rectifying method is proposed to reduce distortions that might occur due to lens distortions, error accumulation and the difficulties of optical imaging in an underwater medium. The topology estimation problem is addressed by means of an augmented state and extended Kalman filter combined framework, aimed at minimising the total number of matching attempts and simultaneously obtaining the best possible trajectory. Potential image pairs are predicted by taking into account the uncertainty in the trajectory. The contribution of matching an image pair is investigated using information theory principles. Lastly, a different solution to the topology estimation problem is proposed in a bundle adjustment framework. Innovative aspects include the use of fast image similarity criterion combined with a Minimum spanning tree (MST) solution, to obtain a tentative topology. This topology is improved by attempting image matching with the pairs for which there is the most overlap evidence. Unlike previous approaches for large-area mosaicing, our framework is able to deal naturally with cases where time-consecutive images cannot be matched successfully, such as completely unordered sets. Finally, the efficiency of the proposed methods is discussed and a comparison made with other state-of-the-art approaches, using a series of challenging datasets in underwater scenarios