Miracle-dz/UniFAR-FTUs huggingface dataset:
Norfloxacino a 0,3% no tratamento de conjuntivites a blefaroconjuntivites agudas

Foram estudadas a eficacia e a tolerabilidade do colirio de norfloxacina a 0,3% em 103 pacientes com diagnostico de conjuntivite ou blefaroconjuntivite aguda de etiologia presumivelmente bacteriana. Observou-se melhora acentuada do quadro clinico ja nas 24 a 48 horas apos o inicio da medicacao e em 91,3% dos casos nao ocorreram reacoes adversas. Os agentes etiologicos mais frequentes foram S. epidermidis e S. aureus e a sensibilidade in vitro de norfloxacina a essas bacterias foi respectivamente de 91,2% e 91,3%. Os resultados confirmam na clinica a potencialidade demonstrada nos estudos in vitro do uso oftalmologico do norfloxacino para o tratamento de infeccoes superficiais do olho e anexos
Speech recognition by clustering wavelet and PLP coefficients

This thesis explores the use of K-means clustering, wavelets and perceptual linear predictive (PLP) analysis for speech recognition. First, we would like to compare the performance of this method to those of previous speech recognition techniques. Next, we want to test if both wavelet and PLP coefficients are important to the analysis. Finally, we want to try out various means of improving the clustering method. The task of phonetic classification is used as the basis of comparison. Three different sets of phonemes are chosen from the TIMIT database: 16 vowels, 24 consonants and 39 phonetic classes. Coefficients of the Haar wavelet transform and the 5th order PLP analysis are combined to form a 42-dimensional vector for each phoneme. Clusters of phoneme vectors obtained by K-means clustering are then used to classify test vectors. Classification experiments using the NIST train and test sets show that independent clustering of phonemes with proportional phoneme emphasis is the best clustering strategy. It yields an accuracy of 55.4% for vowel classification, 54.6% for consonant classification and 50.9% for phoneme classification. Tests with waveletonly vectors and PLP-only vectors show that both the wavelet transform and PLP analysis are significantly important to the phonetic classifier. Results also show that wavelet coefficients are useful for detecting sound transitions, which are abundant in consonants. Thesis Supervisor: Kenneth Yip Title: Visiting Assistant Professor
Optimising the Java virtual machine instruction set

The implementation of statically and dynamically optimised virtual machines for resource constrained devices does not appear easy without trade offs between functionality, performance and memory use. Java virtual machines that interpret Java bytecode appear to be the answer, but are inherently slow. Avenues have been explored that can help with this, all of which appear to be equally viable. Our attention is turned towards the actual driving force behind the machine (the instruction set) and shows that through the use of simple, well established methodology’s, a more compact instruction set can be derived for the Java virtual machine through the analysis of static properties of application data. This is desirable for a number of reasons allowing us to optimise implementations of virtual machines without explicitly modifying the way in which a Java virtual machine works. This dissertation describes the implementation of a system for extracting extensive statistics from a number of Java applications, and makes use of the statistics to describe a number of possible amendments to the existing Java virtual machine instruction set.
Analytical Models for Decision Making

Health care systems are complex and, as a result, it is often unclear what the effects of changes in policy or service provision might be. At the same time, resources for health care tend to be in short supply, which means that public health practitioners have to make difficult decisions. This book describes the quantitative and qualitative methods that can help decision-makers to structure and clarify difficult problems and to explore the implications of pursuing different options. The accompanying CD ROM provides the opportunity to try out some of the proposed solutions. The book examines: models and decision-making in health care; methods for clarifying complex decisions; models for service planning and resource allocation; and modelling for evaluating changes in systems. Series Editors: Rosalind Plowman and Nicki Thorogood.
A 126 dB linear switched-capacitor delta-sigma modulator

Low-frequency measurement applications where low power, high dynamic range and high linearity are important naturally migrate toward oversampling converters. Measuring seismic activity is one such application that requires at least 120 dB S/D. The switched-capacitor delta-sigma modulator presented in this paper achieves the above goals with single-ended linearity in excess of 120 dB. Various distortion mechanisms in switched-capacitor topologies are explained along with solutions. <<ETX>>
Least constraining time-slot allocation in GMPLS optical TDM networks and optimization of optical buffering

Optical Time Division Multiplexing (OTDM) in optical networks is a bandwidth sharing technique that organizes access to a shared wavelength in equal time-slots organized in repeated frames. In this case, a transmission channel can be established at the time-slot level instead of using the full wavelength. The main advantage of this technique is to allow several low speed communication channels to coexist on the same high speed optical wavelength, and hence to make effective use of the enormous bandwidth available on a single wavelength. On the other hand, the major problem with OTDM is the time slot continuity constraint in an OTDM channel, which is similar to the wavelength continuity in a WDM channel. Due to this constraint, time slot contentions can exist in the network if proper scheduling and slot reservation techniques are not employed. Basically, the adopted time slots must be free on all links throughout the communication route in order to successfully reserve a communication channel. In addition, to mitigate the effect of slot continuity constraint on bandwidth utilization, appropriate time slot buffering (or interchanging) is often employed. Previous work assumed the deployment of Optical Time-Slot Interchangers (OTSI) to solve the contention problems regardless of their industrial feasibility. In addition, other work considered very basic reservation schemes to achieve proper scheduling, such as the First Fit (FF), Random Fit (RF), and Least Loaded (LL) schemes. In this thesis, we propose a new time-slot reservation scheme for OTDM networks without buffering to significantly improve the performance and eliminate the buffering overhead. It is the Least Constraining (LC) slot reservation scheme which allocates resources having the lowest possible constraints on other resources in the network. In addition, we define a distributed scheme to deploy the LC approach in GMPLS networks, and prove that the same performance level can be maintained by a distributed signaling protocol. Finally, we propose an optimized optical buffering technique to achieve close to optimum performance when the LC reservation approach is not used. It helps in building effective time slot synchronization devices used between adjacent node pairs.
Risk Assessment and Decision Analysis with Bayesian Networks

Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk. com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software.
Early Detection of Melanoma using Color and Shape Geometry Feature

Melanoma occurrence rates contain be increasing for the earlier 3 decades. The majority folks analyzed with non-melanoma carcinoma contain higher prospects to cure, however malignant melanoma endurance rates are low compare to different carcinoma varieties. It is important that one in 5 Americans will grow skin cancer in their life, and generally, one American expires from skin cancer each hour. A system to obviate this kind of skin cancer is being scheduled and is very in-demand. Initial detection of melanoma is one of the key factors to increment the chance of remedy significantly. Malignant melanomas are asymmetrical and have aberrant borders with rages and notched edges, thus analyzing the form of the skin lesion is consequential for melanoma early detection and aversion. In this paper, we have a tendency to introduce an automatic skin lesion segmentation and analysis for premature detection and obviation predicated on color and shape geometry. The system additionally incorporates extra feature sets such as color to find the wound type. In our planned system, we use PH2 Dermoscopy image information. This image info contains a complete of fifty dermoscopy pictures of lesions, together with traditional, malignant melanoma and atypical cases. Our approach of analyzing the form pure mathematics and therefore the color are going to be subsidiary to detect atypical lesions afore it grows and becomes a melanoma case.
Crowdsourcing Construction Activity Analysis from Jobsite Video Streams

AbstractThe advent of affordable jobsite cameras is reshaping the way on-site construction activities are monitored. To facilitate the analysis of large collections of videos, research has focused on addressing the problem of manual workface assessment by recognizing worker and equipment activities using computer-vision algorithms. Despite the explosion of these methods, the ability to automatically recognize and understand worker and equipment activities from videos is still rather limited. The current algorithms require large-scale annotated workface assessment video data to learn models that can deal with the high degree of intraclass variability among activity categories. To address current limitations, this study proposes crowdsourcing the task of workface assessment from jobsite video streams. By introducing an intuitive web-based platform for massive marketplaces such as Amazon Mechanical Turk (AMT) and several automated methods, the intelligence of the crowd is engaged for interpreting jobsite vid.
Learning and relearning in Boltzmann machines

This chapter contains sections titled: Relaxation Searches, Easy and Hard Learning, The Boltzmann Machine Learning Algorithm, An Example of Hard Learning, Achieving Reliable Computation with Unreliable Hardware, An Example of the Effects of Damage, Conclusion, Acknowledgments, Appendix: Derivation of the Learning Algorithm, References
Semantic and Pragmatic Dependencies of Information Systems

Apparatus for mining coal or other mineable material, of the continuous or mobile type, having a cutter head operative to engage and work the mine face, and having associated therewith one or more vacuum lines or air suction conduits which are critically oriented relative to the working face and the cutter head. A main vacuum line may be employed to pneumatically convey the freshly mined, lump size coal to ground level, or to a subsurface grinder, or other site remote from the mine face. One or more auxillary vacuum lines may be positioned to terminate adjacent the mine roof and floor, and in close proximity to the working face, to scavenge methane, carbon dioxide, carbon monoxide and coal dust.
The Fabularium: a reflective case study of practice-as-research into outdoor performance training and graduate enterprise delivered at Coventry University 2010‒2017

This article documents the formation and development an outdoor performance company that has emerged from pedagogical research and practice undertaken since 2010. The semi-formal training of (initially undergraduate) performers has focused upon popular outdoor performance skillsets, including half and full mask work; puppetry; acrobatics; stilt walking; fooling; walkabouts; drum processions; story-telling vignettes and songs. The work has explicitly drawn upon historical traditions, reinterpreting the mummers’ bestiary and Commedia dell’Arte, as well as other twentieth-century approaches to mask performance. Training models have emerged which bear comparison to historical models for training in popular performance. There is a sense of a journeyman’s approach to training and skills acquisition, as older performers pass on personal repertoires of physical routines, sight gags and tricks, audience interaction and patter etc. Students also work as ‘apprentices’ alongside professional puppet and mask makers and peer-to-peer training is discussed whereby previously trained Fabularium performers pass on the repertoire to new performers. The apparent continuity of approach is examined as traditional popular forms are assimilated and passed on via these teaching and training methods.
Simulation of semiautonomy mode for ibis mobile robot with analysis of sensor failure tolerance

: This work is concerned on sensitivity analysis of semiautonomy algorithm of mobile combat robot to environmental sensors’ damage. The construction of the robot, semiautonomy algorithm and used sensors have been described. This algorithm takes into account environmental sensors’ damage. Simulation research results of semiautonomy algorithm using Matlab/Simulink package was presented. This research was performed for normal environmental sensors’ operation and for selected sensors’ damage. On that basis, sensitivity of semiau-tonomy algorithm to selected environmental sensors damage was tested.
A Deep Graphical Model for Spelling Correction

We propose a deep graphical model for the correction of isolated spelling errors in text. The model is a deep autoencoder consisting of a stack of Restricted Boltzmann Machines, and learns to associate errorfree strings represented as bags of character n-grams with bit strings. These bit strings can be used to find nearest neighbor matches of spelling errors with correct words. This is a novel application of a deep learning semantic hashing technique originally proposed for document retrieval. We demonstrate the effectiveness of our approach for two corpora of spelling errors, and propose a scalable correction procedure based on small sublexicons.
Effect of low-level laser therapy (GaAlAs - λ660 nm) on muscle function

Introduction:Low-level laser therapy (LLLT) is effective in preventing fatigue and in stimulating the microcirculation and cellular activity. In this study, we examined the effect of LLLT on injured tibial muscle in vivo by assessing muscle function during fatigue.MethodsTwenty-four male mice were used. Each mouse received an injection of sterile 0.9% saline solution (50 µL) in the right tibialis anterior muscle, after which the tendon of the muscle was exposed, connected to an isometric transducer and subjected to a resting tension of 1 g. A bipolar electrode was attached to the tibial nerve for electrical stimulation. The mice were randomly allocated to one of two groups: G1 (control: 3 h – n=8 and 9 h – n=5) and G2 (treated with GaAlAs laser, λ660 nm, 35 mW, 0.6 J, 17 s: 3 h – n=6 and 9 h – n=5). ResultsIn G1 mice, the amplitude of the tetanic contracture in response to induced fatigue remained unchanged during six consecutive tetani. The amplitude of the tetanic contractions in response to electrical stimulation (4-8 mV) was also unchanged. These results indicated muscle intactness in response to the load imposed by tetanus. In G2 mice, there was an increase in the amplitude of contraction after 3 h and 9 h when compared to G1 at 83% tetanus.ConclusionThese results indicate that exposure of muscle to LLLT enhanced the contractile force and increased the resistance to muscle fatigue without causing morphological damage to cellular structures.
Evaluación y selección de software: extracción automática de texto en ficheros PDF

Se trata de un proyecto de consultoria/evaluacion tecnologica con el objeto de definir un sistema para la extraccion "estructurada" del texto de articulos cientificos (concretamente en el area de biomedicina) almacenados en formato PDF. PubMed Central (www.pubmedcentral.nih.gov) es el archivo digital del NIH estadounidense (National Institutes of Health) que ofrece acceso a los articulos publicados en las areas de biomedicina y ciencias de la vida . PubMed Central ha definido un estandar (en formato DTD) para la estructuracion del contenido de dichos articulos. Sin embargo el uso de este estandar no esta muy extendido y la mayoria de publicaciones se encuentran en formato PDF. La cantidad de publicaciones hoy en dia en tan grande que hace casi imposible encontrar la informacion que pueda estar relacionada con un proyecto sin un formato estandar. De ahi nace la iniciativa del NIH y la necesidad de una herramienta para convertir documentos en otros formatos a un mismo estandar. En la actualidad existen diversos programas para la conversion de archivos en formato PDF a texto, el objetivo del proyecto es determinar cual seria el software mas adecuado para esta conversion. En un primer analisis se han realizado varias pruebas con algunos de los programas mas destacados con distinto tipo de licencias. Entre ellos se han elegido los mejores y se ha hecho un analisis mas exhaustivo comprobando todas las funcionalidades de cada uno de ellos. Cabe destacar el XPDF cuyo codigo fuente esta disponible bajo licencia GNU y que permitiria trabajar sobre el para una futura adaptacion al formato NCBI DTD. [ABSTRACT] The project is about the technology consulting/evaluation for the definition of a “structured” extraction system of text for scientific publications(more exactly in the biomedicine area) stored in PDF format. PubMed Central (www.pubmedcentral.nih.gov) is the U.S. National Institutes of Health (NIH) digital archive of biomedical and life sciences journal literature. PubMed Central has established a standard (in DTD format) for the organization of article contents. However the use of this standard is not very spread and nowadays most of publications are in PDF format. The quantity of publications is so huge that make it impossible to find the related information to a project without a standard format. This was the reason for the NIH initiative and the need of a tool to convert documents in other formats to a common standard. Nowadays there are different programs for the conversion of PDF formatted files to text files,the goal of this project is to determine wich would be the most relevant software to make this convertion. In a first analysis we have done different tests with some of the best programs with different licence type. Among them we have chosen the bests and make a more detailed test checking all available functions. It is worth pointing out XPDF that its source code is available under the GNU licence so it would allow to work on it for a future adaptation to the NCBI DTD format.
Public Health Information Retrieval from Non-health Databases

This study examines the extent to which non-health databases index public health and healthcare related journals. The field of public health and healthcare is unique and multidisciplinary and therefore presents some challenges for researchers looking for published literature in the field. This challenge forces researchers to look beyond databases like Medline and search a wide array of databases in various fields. A list of journal titles from non-health databases in various fields was used to compare title coverage in Medline (Ovid). Databases used in this study are Canadian Business & Current Affairs (CBCA) Complete, which is a multidisciplinary database; ABI/Inform covering business literature; Public Affairs Information Services (PAIS); EconLit; PsycInfo focusing only on public health journals and eliminating psychology specific journals; Sociological Abstracts; and Women’s Studies international.
Thèse de doctorat : Algorithmes de classification répartis sur le cloud

Les themes de recherche abordes dans ce manuscrit sont inspires et motives de problemes concrets rencontres par la societe Lokad. Ils ont trait principalement a la parallelisation d'algorithmes de classification non-supervisee (clustering) sur des plateformes de Cloud Computing. Le chapitre 2 propose un tour d'horizon de ces technologies. Nous y presentons d'une maniere generale le Cloud Computing comme plateforme de calcul. Le chapitre 3 presente plus en avant l'offre cloud de Microsoft : Windows Azure. Le chapitre suivant analyse certains enjeux techniques de la conception d'applications cloud et propose certains elements d'architecture logicielle pour de telles applications. Le chapitre 5 propose une analyse du premier algorithme de classification etudie : le Batch K-Means. En particulier, nous approfondissons comment les versions reparties de cet algorithme doivent etre adaptees a une architecture cloud. Nous y montrons l'impact des couts de communication sur l'efficacite de cet algorithme lorsque celui-ci est implemente sur une plateforme cloud. Les chapitres 6 et 7 presentent un travail de parallelisation d'un autre algorithme de classification : l'algorithme de Vector Quantization (VQ). Dans le chapitre 6 nous explorons quels schemas de parallelisation sont susceptibles de fournir des resultats satisfaisants en terme d'acceleration de la convergence. Le chapitre 7 presente une implementation de ces schemas de parallelisation. Les details pratiques de l'implementation soulignent un resultat de premiere importance : c'est le caractere en ligne du VQ qui permet de proposer une implementation asynchrone de l'algorithme reparti, supprimant ainsi une partie des problemes de communication rencontres lors de la parallelisation du Batch K-Means.
Automatic feature extraction and recognition of fingerprint images

A technique for the recognition of fingerprint images is described in this paper. Fingerprint images are preprocessed by using a set of contextual filters first and then thinned to extract the fingerprint "minutiae" features. As the images are noisy, there are many spurious minutiae. These spurious minutiae can be detected and deleted efficiently by a proposed method. The method for matching fingerprint images is also given. The usage of the technique in this paper allows for fairly high degree of noise tolerance.