Purification of complex biopharmaceuticals with new processes, advanced analytics and computer-aided process design tools

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

A distributed environment for virtual and/or real experiments for underwater robots

This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments

What Was I Thinking? Eye-Tracking Experiments Underscore the Bias that Architecture Exerts on Nuclear Grading in Prostate Cancer.

We previously reported that nuclear grade assignment of prostate carcinomas is subject to a cognitive bias induced by the tumor architecture. Here, we asked whether this bias is mediated by the non-conscious selection of nuclei that "match the expectation" induced by the inadvertent glance at the tumor architecture. 20 pathologists were asked to grade nuclei in high power fields of 20 prostate carcinomas displayed on a computer screen. Unknown to the pathologists, each carcinoma was shown twice, once before a background of a low grade, tubule-rich carcinoma and once before the background of a high grade, solid carcinoma. Eye tracking allowed to identify which nuclei the pathologists fixated during the 8 second projection period. For all 20 pathologists, nuclear grade assignment was significantly biased by tumor architecture. Pathologists tended to fixate on bigger, darker, and more irregular nuclei when those were projected before kigh grade, solid carcinomas than before low grade, tubule-rich carcinomas (and vice versa). However, the morphometric differences of the selected nuclei accounted for only 11% of the architecture-induced bias, suggesting that it can only to a small part be explained by the unconscious fixation on nuclei that "match the expectation". In conclusion, selection of « matching nuclei » represents an unconscious effort to vindicate the gravitation of nuclear grades towards the tumor architecture.

Determination of hydraulic properties of a tropical soil of Hawaii using column experiments and inverse modeling

A method for determining soil hydraulic properties of a weathered tropical soil (Oxisol) using a medium-sized column with undisturbed soil is presented. The method was used to determine fitting parameters of the water retention curve and hydraulic conductivity functions of a soil column in support of a pesticide leaching study. The soil column was extracted from a continuously-used research plot in Central Oahu (Hawaii, USA) and its internal structure was examined by computed tomography. The experiment was based on tension infiltration into the soil column with free outflow at the lower end. Water flow through the soil core was mathematically modeled using a computer code that numerically solves the one-dimensional Richards equation. Measured soil hydraulic parameters were used for direct simulation, and the retention and soil hydraulic parameters were estimated by inverse modeling. The inverse modeling produced very good agreement between model outputs and measured flux and pressure head data for the relatively homogeneous column. The moisture content at a given pressure from the retention curve measured directly in small soil samples was lower than that obtained through parameter optimization based on experiments using a medium-sized undisturbed soil column.

Computer-simulation study of magnetic relaxation in anisotropic magnetic systems

We present a computer-simulation study of the effect of the distribution of energy barriers in an anisotropic magnetic system on the relaxation behavior of the magnetization. While the relaxation law for the magnetization can be approximated in all cases by a time logarithmic decay, the law for the dependence of the magnetic viscosity with temperature is found to be quite sensitive to the shape of the distribution of barriers. The low-temperature region for the magnetic viscosity never extrapolates to a positive no-null value. Moreover our computer simulation results agree reasonably well with some recent relaxation experiments on highly anisotropic single-domain particles.

A Computer program for estimating population size by the removal method

A BASIC computer program (REMOVAL) was developed to compute in a VAXNMS environment all the calculations of the removal method for population size estimation (catch-effort method for closed populations with constant sampling effort). The program follows the maximum likelihood methodology,checks the failure conditions, applies the appropriate formula, and displays the estimates of population size and catchability, with their standard deviations and coefficients of variation, and two goodness-of-fit statistics with their significance levels. Data of removal experiments for the cyprinodontid fish Aphanius iberus in the Alt Emporda wetlands are used to exemplify the use of the program

Seguiment d'extremitats de ratolins en experiments optogenètics

L'objectiu principal d'aquest treball és aplicar tècniques de visió articial per aconseguir localitzar i fer el seguiment de les extremitats dels ratolins dins l'entorn de prova de les investigacions d'optogenètica del grup de recerca del Neuroscience Institute de la Universitat de Princeton, Nova Jersey.

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is oftenassociated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcificationsis performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcificationshave been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the senseof adding new features not only related to the shape

Brain Computer Interface for Virtual Reality Control

A brain-computer interface (BCI) is a new communication channel between the human brain and a computer. Applications of BCI systems comprise the restoration of movements, communication and environmental control. In this study experiments were made that used the BCI system to control or to navigate in virtual environments (VE) just by thoughts. BCI experiments for navigation in VR were conducted so far with synchronous BCI and asynchronous BCI systems. The synchronous BCI analyzes the EEG patterns in a predefined time window and has 2 to 3 degrees of freedom.

VVER-440 Thermal Hydraulics as a Computer Code Validation Challenge

This thesis concentrates on the validation of a generic thermal hydraulic computer code TRACE under the challenges of the VVER-440 reactor type. The code capability to model the VVER-440 geometry and thermal hydraulic phenomena specific to this reactor design has been examined and demonstrated acceptable. The main challenge in VVER-440 thermal hydraulics appeared in the modelling of the horizontal steam generator. The major challenge here is not in the code physics or numerics but in the formulation of a representative nodalization structure. Another VVER-440 specialty, the hot leg loop seals, challenges the system codes functionally in general, but proved readily representable. Computer code models have to be validated against experiments to achieve confidence in code models. When new computer code is to be used for nuclear power plant safety analysis, it must first be validated against a large variety of different experiments. The validation process has to cover both the code itself and the code input. Uncertainties of different nature are identified in the different phases of the validation procedure and can even be quantified. This thesis presents a novel approach to the input model validation and uncertainty evaluation in the different stages of the computer code validation procedure. This thesis also demonstrates that in the safety analysis, there are inevitably significant uncertainties that are not statistically quantifiable; they need to be and can be addressed by other, less simplistic means, ultimately relying on the competence of the analysts and the capability of the community to support the experimental verification of analytical assumptions. This method completes essentially the commonly used uncertainty assessment methods, which are usually conducted using only statistical methods.

A brain-computer interface for navigation in virtual reality

L'interface cerveau-ordinateur (ICO) décode les signaux électriques du cerveau requise par l’électroencéphalographie et transforme ces signaux en commande pour contrôler un appareil ou un logiciel. Un nombre limité de tâches mentales ont été détectés et classifier par différents groupes de recherche. D’autres types de contrôle, par exemple l’exécution d'un mouvement du pied, réel ou imaginaire, peut modifier les ondes cérébrales du cortex moteur. Nous avons utilisé un ICO pour déterminer si nous pouvions faire une classification entre la navigation de type marche avant et arrière, en temps réel et en temps différé, en utilisant différentes méthodes. Dix personnes en bonne santé ont participé à l’expérience sur les ICO dans un tunnel virtuel. L’expérience fut a était divisé en deux séances (48 min chaque). Chaque séance comprenait 320 essais. On a demandé au sujets d’imaginer un déplacement avant ou arrière dans le tunnel virtuel de façon aléatoire d’après une commande écrite sur l'écran. Les essais ont été menés avec feedback. Trois électrodes ont été montées sur le scalp, vis-à-vis du cortex moteur. Durant la 1re séance, la classification des deux taches (navigation avant et arrière) a été réalisée par les méthodes de puissance de bande, de représentation temporel-fréquence, des modèles autorégressifs et des rapports d’asymétrie du rythme β avec classificateurs d’analyse discriminante linéaire et SVM. Les seuils ont été calculés en temps différé pour former des signaux de contrôle qui ont été utilisés en temps réel durant la 2e séance afin d’initier, par les ondes cérébrales de l'utilisateur, le déplacement du tunnel virtuel dans le sens demandé. Après 96 min d'entrainement, la méthode « online biofeedback » de la puissance de bande a atteint une précision de classification moyenne de 76 %, et la classification en temps différé avec les rapports d’asymétrie et puissance de bande, a atteint une précision de classification d’environ 80 %.