Web Service Composition Systems for the Web Service Challenge - A Detailed Review

This report gives a detailed discussion on the system, algorithms, and techniques that we have applied in order to solve the Web Service Challenges (WSC) of the years 2006 and 2007. These international contests are focused on semantic web service composition. In each challenge of the contests, a repository of web services is given. The input and output parameters of the services in the repository are annotated with semantic concepts. A query to a semantic composition engine contains a set of available input concepts and a set of wanted output concepts. In order to employ an offered service for a requested role, the concepts of the input parameters of the offered operations must be more general than requested (contravariance). In contrast, the concepts of the output parameters of the offered service must be more specific than requested (covariance). The engine should respond to a query by providing a valid composition as fast as possible. We discuss three different methods for web service composition: an uninformed search in form of an IDDFS algorithm, a greedy informed search based on heuristic functions, and a multi-objective genetic algorithm.

A Vector Signal Processing Approach to Color

Surface (Lambertain) color is a useful visual cue for analyzing material composition of scenes. This thesis adopts a signal processing approach to color vision. It represents color images as fields of 3D vectors, from which we extract region and boundary information. The first problem we face is one of secondary imaging effects that makes image color different from surface color. We demonstrate a simple but effective polarization based technique that corrects for these effects. We then propose a systematic approach of scalarizing color, that allows us to augment classical image processing tools and concepts for multi-dimensional color signals.

Comparación de dos técnicas anestésicas con la producción de metabolitos de estrés en lactantes llevados a cirugía cardiaca

A través del tiempo las técnicas anestésicas basadas en opioides y especialmente en fentanyl han sido las más frecuentemente utilizadas en cirugía cardiaca pediátrica con circulación extracorpórea (CEC). La población pediátrica y en especial los niños menores de 10 kilos de peso tienen mayor susceptibilidad a las complicaciones postoperatorias, una de las razones para esta especial susceptibilidad es la respuesta al estrés y la reacción inflamatoria sistémica que desencadena la CEC en estos pacientes. La utilización de nuevos opioides (Remifentanil) más potentes, puede tener un impacto importante en la disminución del estrés metabólico desencadenado por la cirugía cardiaca. Mediante un estudio de cohortes realizado con los pacientes menores de 10 kilogramos de peso llevados a cirugía cardiaca con CEC se expusieron a dos diferentes técnicas anestésicas: la técnica “tradicional” basada en Fentanyl y otra basada en Remifentanil, se midieron las covariables que pudieran provocar altos niveles de estrés metabólico y se tomaron niveles basales y postoperatorios de tres metabolitos relacionados con el estrés (Lactato, Glucosa y Cortisol). Los resultados del estudio muestran grupos comparables en las mediciones basales de metabolitos de estrés y características clínicas, además de una relación, estadísticamente significativa, entre una menor producción de glucosa durante la CEC en los pacientes que son anestesiados con infusiones de remifentanil, los demás metabolitos no tuvieron relación con la técnica anestésica. Estos resultados abren caminos para la realización de estudios clínicos con el objetivo de establecer terapéuticas que permitan la disminución de la morbi-mortalidad asociada a cirugía cardiaca.

Comparación de costo-efectividad entre dos técnicas anestésicas: anestesia con sevofluoraneremifentanil frente a isofluorane-remifentanil

Nos encontramos en la era de la optimización de costos, por lo que es necesario realizar estudios farmacoeconómicos para identificar la costo- efectividad de los anestésicos actuales. Metodología: este estudio prospectivo, cegado al paciente, comparó los costos directos, los tiempos de recuperación y satisfacción de 45 pacientes que se asignaron aleatoriamente a dos grupos de anestesia balanceada (grupo sevofluoraneremifentanil n = 24 o grupo isofluoraneremifentanil n = 21) que iban a ser sometidos a cirugías de otorrinolaringología. Resultados: los tiempos de recuperación temprana (apertura ocular, respuesta a comandos, extubación, orientación y salida de sala) fueron menores en el grupo ISO y tuvieron diferencia estadísticamente significativa. Se encontraron datos variables en los costos de adquisición de los halogenados gastados, que fueron menores para el isofluorane, lo cual hacía también menos costosos los insumos anestésicos durante las cirugías; sin embargo, los costos en la sala de cirugía, en recuperación y sala de ambulatorios y los costos totales no mostraron diferencias significativas. La satisfacción fue similar entre los dos grupos. Conclusiones: una técnica basada en sevofluorane-remifentanil no es más costo-efectiva que utilizar isofluorane-remifentanil para pacientes ambulatorios sometidos a cirugías de otorrinolaringología.

Remote sensing of tidal networks and their relation to vegetation

The study of the morphology of tidal networks and their relation to salt marsh vegetation is currently an active area of research, and a number of theories have been developed which require validation using extensive observations. Conventional methods of measuring networks and associated vegetation can be cumbersome and subjective. Recent advances in remote sensing techniques mean that these can now often reduce measurement effort whilst at the same time increasing measurement scale. The status of remote sensing of tidal networks and their relation to vegetation is reviewed. The measurement of network planforms and their associated variables is possible to sufficient resolution using digital aerial photography and airborne scanning laser altimetry (LiDAR), with LiDAR also being able to measure channel depths. A multi-level knowledge-based technique is described to extract networks from LiDAR in a semi-automated fashion. This allows objective and detailed geomorphological information on networks to be obtained over large areas of the inter-tidal zone. It is illustrated using LIDAR data of the River Ems, Germany, the Venice lagoon, and Carnforth Marsh, Morecambe Bay, UK. Examples of geomorphological variables of networks extracted from LiDAR data are given. Associated marsh vegetation can be classified into its component species using airborne hyperspectral and satellite multispectral data. Other potential applications of remote sensing for network studies include determining spatial relationships between networks and vegetation, measuring marsh platform vegetation roughness, in-channel velocities and sediment processes, studying salt pans, and for marsh restoration schemes.

Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.

Structure adaptation of linear MMSE adaptive filters

The tap-length, or the number of the taps, is an important structural parameter of the linear MMSE adaptive filter. Although the optimum tap-length that balances performance and complexity varies with scenarios, most current adaptive filters fix the tap-length at some compromise value, making them inefficient to implement especially in time-varying scenarios. A novel gradient search based variable tap-length algorithm is proposed, using the concept of the pseudo-fractional tap-length, and it is shown that the new algorithm can converge to the optimum tap-length in the mean. Results of computer simulations are also provided to verify the analysis.

Complementarity of neutron reflectometry and ellipsometry for the study of atmospheric reactions at the air–water interface

The combined application of neutron reflectometry (NR) and ellipsometry to determine the oxidation kinetics of organic monolayers at the air–water interface is described for the first time. This advance was possible thanks to a new miniaturised reaction chamber that is compatible with the two techniques and has controlled gas delivery. The rate coefficient for the oxidation of methyl oleate monolayers by gas-phase O3 determined using NR is (5.4 ± 0.6) × 10−10 cm2 per molecule per s, which is consistent with the value reported in the literature but is now better constrained. This highlights the potential for the investigation of faster atmospheric reactions in future studies. The rate coefficient determined using ellipsometry is (5.0 ± 0.9) × 10−10 cm2 per molecule per s, which indicates the potential of this more economical, laboratory-based technique to be employed in parallel with NR. In this case, temporal fluctuations in the optical signal are attributed to the mobility of islands of reaction products. We outline how such information may provide critical missing information in the identification of transient reaction products in a range of atmospheric surface reactions in the future.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Money distribution with intermediation

This pap er analyzes the distribution of money holdings in a commo dity money search-based mo del with intermediation. Intro ducing heterogeneity of costs to the Kiyotaki e Wright ( 1989 ) mo del, Cavalcanti e Puzzello ( 2010) gives rise to a non-degenerated distribution of money. We extend further this mo del intro ducing intermediation in the trading pro cess. We show that the distribution of money matters for savings decisions. This gives rises to a xed p oint problem for the saving function that di cults nding the optimal solution. Through some examples, we show that this friction shrinks the distribution of money. In contrast to the Cavalcanti e Puzzello ( 2010 ) mo del, the optimal solution may not present the entire surplus going to the consumer. At the end of the pap er, we present a strong result, for a su cient large numb er of intermediaries the distribution of money is degenerated.

Spontaneous Blinking in Patients With Graves' Upper Eyelid Retraction

Purpose: To describe spontaneous blink kinematics in Graves' upper eyelid retraction (UER).Methods: The magnetic search coil technique was used to record spontaneous blinks of 15 healthy subjects (aged 23-56 years, 15 eyelids) and 15 patients with Graves' UER (aged 22-62 years, 15 eyelids) during a 5-min period of video observation, and the signals were digitized at 200 Hz (12 bits). Overall, a total of 2,798 blinks were recorded for the controls and 1,860 for the patients. The distance between pupil center and upper eyelid margin in the primary position of gaze (MRD) was measured with the Image J software.Results: The blinking rate of patients was lower than that of control subjects, with a mean (+/-SEM) blinking rate (blinks/min) of 13.0 +/- 1.7 for patients and of 20.0 +/- 2.1 for the controls (t = 2.58, P = 0.016). There were no statistically significant differences in blink amplitude between controls (22.7 +/- 3.1 degrees) and Graves' patients (24.7 +/- 3.3 degrees). However, while only 22% of the blinks performed by controls were smaller than MRD, this rate was 78% for patients. In addition, in blinks larger than 25, patients showed lower down-phase velocity than controls.Conclusions: Patients with Graves' UER show reduced blinks rates and abnormal blink kinematics, which might be related to the development of exposure keratitis in this disease.

Spontaneous Interblink Time Distributions in Patients with Graves' Orbitopathy and Normal Subjects

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

3-D reconstruction by extended depth-of-field in failure analysis - Case study I: Qualitative fractographic investigation of fractured bolts in a partial valve

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Smart structures health monitoring using artificial neural network

This paper presents a non-model based technique to detect and locate structural damage with the use of artificial neural networks. This method utilizes high frequency structural excitation (typically greater than 30 kHz) through a surface-bonded piezoelectric sensor/actuator to detect changes in structural point impedance due to the presence of damage. Two sets of artificial neural networks were developed in order to detect, locate and characterize structural damage by examining changes in the measured impedance curves. A simulation beam model was developed to verify the proposed method. An experiment was successfully performed in detecting damage on a 4-bay structure with bolted-joints, where the bolts were progressively released.

RAPD genomic fingerprinting differentiates Thiobacillus ferrooxidans strains

The PCR-based technique, involving the random amplification of polymorphic DNA (RAPD), was optimized and used for assessing genomic variability among eight Thiobacillus ferrooxidans strains. RAPD fingerprints presented variation for the thirty primers used, giving a total of 269 polymorphic bands. Similarity coefficients between the strains were calculated, and UPGMA cluster analysis was used to generate a dendrogram showing relationships among them. Most primers divided T. ferrooxidans strains in two distinct groups - Group 1: S, SSP, V3, AMF and Group 2: CMV, FG-460, I-35, LR. We observed that the T. ferrooxidans strains used in this work have a high degree of genomic diversity and that RAPD is a powerful method to differentiate them.