830 resultados para AUTOMATED DOCKING
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This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the autonomous surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended Kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.
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Phosphatase and tensin homologue (PTEN) protein belongs to the family of protein tyrosine phos-phatase. Mutations on the phosphatase and tensin homologue (PTEN) protein are highly observed in diverse types of human tumors, being mostly identified on the phosphatase domain of the protein. Although PTEN is a modular protein composed by a phosphatase domain and a C2 domain for mem-brane anchoring, this work aimed at developing a minimal version of PTEN´s phosphatase domain. The minimal version (Small Domain) comprises a 28 residue peptide, with the PTEN 8-mer catalytic peptide accommodated between a α-helix and β-turn as observed in PTEN native structure. Firstly, a de novo prediction of the Small Domain´s secondary structure was carried out by molecular modeling tools. The stability of the predicted structures were then evaluated by Molecular Dynamics. Automated molecular docking of PTEN natural substrate PIP3, its analogue (Inositol) and a PTEN inhibitor (L-tar-tare) were performed with the modeled structure, and PTEN used as a positive control. The gene en-coding for Small Domain was designed and cloned into an expression vector at N-terminal of Green Fluorescence Protein (GFP) encoding gene. The fusion protein was then expressed in Escherichia coli cells. Different expression conditions have been explored for the production of the fusion protein to minimize the formation of inclusion bodies.
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Purpose: To investigate the accuracy of 4 clinical instruments in the detection of glaucomatous damage. Methods: 102 eyes of 55 test subjects (Age mean = 66.5yrs, range = [39; 89]) underwent Heidelberg Retinal Tomography (HRTIII), (disc area<2.43); and standard automated perimetry (SAP) using Octopus (Dynamic); Pulsar (TOP); and Moorfields Motion Displacement Test (MDT) (ESTA strategy). Eyes were separated into three groups 1) Healthy (H): IOP<21mmHg and healthy discs (clinical examination), 39 subjects, 78 eyes; 2) Glaucoma suspect (GS): Suspicious discs (clinical examination), 12 subjects, 15 eyes; 3) Glaucoma (G): progressive structural or functional loss, 14 subjects, 20 eyes. Clinical diagnostic precision was examined using the cut-off associated with the p<5% normative limit of MD (Octopus/Pulsar), PTD (MDT) and MRA (HRT) analysis. The sensitivity, specificity and accuracy were calculated for each instrument. Results: See table Conclusions: Despite the advantage of defining glaucoma suspects using clinical optic disc examination, the HRT did not yield significantly higher accuracy than functional measures. HRT, MDT and Octopus SAP yielded higher accuracy than Pulsar perimetry, although results did not reach statistical significance. Further studies are required to investigate the structure-function correlations between these instruments.
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In this article, we show how the use of state-of-the-art methods in computer science based on machine perception and learning allows the unobtrusive capture and automated analysis of interpersonal behavior in real time (social sensing). Given the high ecological validity of the behavioral sensing, the ease of behavioral-cue extraction for large groups over long observation periods in the field, the possibility of investigating completely new research questions, and the ability to provide people with immediate feedback on behavior, social sensing will fundamentally impact psychology.
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Several automated reversed-phase HPLC methods have been developed to determine trace concentrations of carbamate pesticides (which are of concern in Ontario environmental samples) in water by utilizing two solid sorbent extraction techniques. One of the methods is known as on-line pre-concentration'. This technique involves passing 100 milliliters of sample water through a 3 cm pre-column, packed with 5 micron ODS sorbent, at flow rates varying from 5-10 mUmin. By the use of a valve apparatus, the HPLC system is then switched to a gradient mobile phase program consisting of acetonitrile and water. The analytes, Propoxur, Carbofuran, Carbaryl, Propham, Captan, Chloropropham, Barban, and Butylate, which are pre-concentrated on the pre-column, are eluted and separated on a 25 cm C-8 analytical column and determined by UV absorption at 220 nm. The total analytical time is 60 minutes, and the pre-column can be used repeatedly for the analysis of as many as thirty samples. The method is highly sensitive as 100 percent of the analytes present in the sample can be injected into the HPLC. No breakthrough of any of the analytes was observed and the minimum detectable concentrations range from 10 to 480 ng/L. The developed method is totally automated for the analysis of one sample. When the above mobile phase is modified with a buffer solution, Aminocarb, Benomyl, and its degradation product, MBC, can also be detected along with the above pesticides with baseline resolution for all of the analytes. The method can also be easily modified to determine Benomyl and MBC both as solute and as particulate matter. By using a commercially available solid phase extraction cartridge, in lieu of a pre-column, for the extraction and concentration of analytes, a completely automated method has been developed with the aid of the Waters Millilab Workstation. Sample water is loaded at 10 mL/min through a cartridge and the concentrated analytes are eluted from the sorbent with acetonitrile. The resulting eluate is blown-down under nitrogen, made up to volume with water, and injected into the HPLC. The total analytical time is 90 minutes. Fifty percent of the analytes present in the sample can be injected into the HPLC, and recoveries for the above eight pesticides ranged from 84 to 93 percent. The minimum detectable concentrations range from 20 to 960 ng/L. The developed method is totally automated for the analysis of up to thirty consecutive samples. The method has proven to be applicable to both purer water samples as well as untreated lake water samples.
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We provide an algorithm that automatically derives many provable theorems in the equational theory of allegories. This was accomplished by noticing properties of an existing decision algorithm that could be extended to provide a derivation in addition to a decision certificate. We also suggest improvements and corrections to previous research in order to motivate further work on a complete derivation mechanism. The results presented here are significant for those interested in relational theories, since we essentially have a subtheory where automatic proof-generation is possible. This is also relevant to program verification since relations are well-suited to describe the behaviour of computer programs. It is likely that extensions of the theory of allegories are also decidable and possibly suitable for further expansions of the algorithm presented here.
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La compréhension de processus biologiques complexes requiert des approches expérimentales et informatiques sophistiquées. Les récents progrès dans le domaine des stratégies génomiques fonctionnelles mettent dorénavant à notre disposition de puissants outils de collecte de données sur l’interconnectivité des gènes, des protéines et des petites molécules, dans le but d’étudier les principes organisationnels de leurs réseaux cellulaires. L’intégration de ces connaissances au sein d’un cadre de référence en biologie systémique permettrait la prédiction de nouvelles fonctions de gènes qui demeurent non caractérisées à ce jour. Afin de réaliser de telles prédictions à l’échelle génomique chez la levure Saccharomyces cerevisiae, nous avons développé une stratégie innovatrice qui combine le criblage interactomique à haut débit des interactions protéines-protéines, la prédiction de la fonction des gènes in silico ainsi que la validation de ces prédictions avec la lipidomique à haut débit. D’abord, nous avons exécuté un dépistage à grande échelle des interactions protéines-protéines à l’aide de la complémentation de fragments protéiques. Cette méthode a permis de déceler des interactions in vivo entre les protéines exprimées par leurs promoteurs naturels. De plus, aucun biais lié aux interactions des membranes n’a pu être mis en évidence avec cette méthode, comparativement aux autres techniques existantes qui décèlent les interactions protéines-protéines. Conséquemment, nous avons découvert plusieurs nouvelles interactions et nous avons augmenté la couverture d’un interactome d’homéostasie lipidique dont la compréhension demeure encore incomplète à ce jour. Par la suite, nous avons appliqué un algorithme d’apprentissage afin d’identifier huit gènes non caractérisés ayant un rôle potentiel dans le métabolisme des lipides. Finalement, nous avons étudié si ces gènes et un groupe de régulateurs transcriptionnels distincts, non préalablement impliqués avec les lipides, avaient un rôle dans l’homéostasie des lipides. Dans ce but, nous avons analysé les lipidomes des délétions mutantes de gènes sélectionnés. Afin d’examiner une grande quantité de souches, nous avons développé une plateforme à haut débit pour le criblage lipidomique à contenu élevé des bibliothèques de levures mutantes. Cette plateforme consiste en la spectrométrie de masse à haute resolution Orbitrap et en un cadre de traitement des données dédié et supportant le phénotypage des lipides de centaines de mutations de Saccharomyces cerevisiae. Les méthodes expérimentales en lipidomiques ont confirmé les prédictions fonctionnelles en démontrant certaines différences au sein des phénotypes métaboliques lipidiques des délétions mutantes ayant une absence des gènes YBR141C et YJR015W, connus pour leur implication dans le métabolisme des lipides. Une altération du phénotype lipidique a également été observé pour une délétion mutante du facteur de transcription KAR4 qui n’avait pas été auparavant lié au métabolisme lipidique. Tous ces résultats démontrent qu’un processus qui intègre l’acquisition de nouvelles interactions moléculaires, la prédiction informatique des fonctions des gènes et une plateforme lipidomique innovatrice à haut débit , constitue un ajout important aux méthodologies existantes en biologie systémique. Les développements en méthodologies génomiques fonctionnelles et en technologies lipidomiques fournissent donc de nouveaux moyens pour étudier les réseaux biologiques des eucaryotes supérieurs, incluant les mammifères. Par conséquent, le stratégie présenté ici détient un potentiel d’application au sein d’organismes plus complexes.
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This paper presents a new approach to implement Reed-Muller Universal Logic Module (RM-ULM) networks with reduced delay and hardware for synthesizing logic functions given in Reed-Muller (RM) form. Replication of single control line RM-ULM is used as the only design unit for defining any logic function. An algorithm is proposed that does exhaustive branching to reduce the number of levels and modules required to implement any logic function in RM form. This approach attains a reduction in delay, and power over other implementations of functions having large number of variables.
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In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.
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Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.
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Presentation given at the Al-Azhar Engineering First Conference, AEC’89, Dec. 9-12 1989, Cairo, Egypt. The paper presented at AEC'89 suggests an infinite storage scheme divided into one volume which is online and an arbitrary number of off-line volumes arranged into a linear chain which hold records which haven't been accessed recently. The online volume holds the records in sorted order (e.g. as a B-tree) and contains shortest prefixes of keys of records already pushed offline. As new records enter, older ones are retired to the first volume which is going offline next. Statistical arguments are given for the rate at which an off-line volume needs to be fetched to reload a record which had been retired before. The rate depends on the distribution of access probabilities as a function of time. Applications are medical records, production records or other data which need to be kept for a long time for legal reasons.
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In recent years, researchers in artificial intelligence have become interested in replicating human physical reasoning talents in computers. One of the most important skills in this area is predicting how physical systems will behave. This thesis discusses an implemented program that generates algebraic descriptions of how systems of rigid bodies evolve over time. Discussion about the design of this program identifies a physical reasoning paradigm and knowledge representation approach based on mathematical model construction and algebraic reasoning. This paradigm offers several advantages over methods that have become popular in the field, and seems promising for reasoning about a wide variety of classical mechanics problems.
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SAGA (System for Automated Geographic Analysis) es un SIG libre con capacidades para el manejo y análisis de información tanto vectorial como ráster, con un especial enfoque en esta última. Asimismo, es su enfoque analítico el que constituye su característica más destacable, siendo una herramienta de primer orden para la extracción de información a partir de todo tipo de capas de datos georeferenciados. (...)
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Resolution over FOPL