Signal processing and information fusing algorithms for the synthesis of an alternative electromyogram/eye gaze tracking computer cursor control system

This research pursued the conceptualization and real-time verification of a system that allows a computer user to control the cursor of a computer interface without using his/her hands. The target user groups for this system are individuals who are unable to use their hands due to spinal dysfunction or other afflictions, and individuals who must use their hands for higher priority tasks while still requiring interaction with a computer. ^ The system receives two forms of input from the user: Electromyogram (EMG) signals from muscles in the face and point-of-gaze coordinates produced by an Eye Gaze Tracking (EGT) system. In order to produce reliable cursor control from the two forms of user input, the development of this EMG/EGT system addressed three key requirements: an algorithm was created to accurately translate EMG signals due to facial movements into cursor actions, a separate algorithm was created that recognized an eye gaze fixation and provided an estimate of the associated eye gaze position, and an information fusion protocol was devised to efficiently integrate the outputs of these algorithms. ^ Experiments were conducted to compare the performance of EMG/EGT cursor control to EGT-only control and mouse control. These experiments took the form of two different types of point-and-click trials. The data produced by these experiments were evaluated using statistical analysis, Fitts' Law analysis and target re-entry (TRE) analysis. ^ The experimental results revealed that though EMG/EGT control was slower than EGT-only and mouse control, it provided effective hands-free control of the cursor without a spatial accuracy limitation, and it also facilitated a reliable click operation. This combination of qualities is not possessed by either EGT-only or mouse control, making EMG/EGT cursor control a unique and practical alternative for a user's cursor control needs. ^

A framework for investigating the use of face features to identify spontaneous emotions

Emotion-based analysis has raised a lot of interest, particularly in areas such as forensics, medicine, music, psychology, and human-machine interface. Following this trend, the use of facial analysis (either automatic or human-based) is the most common subject to be investigated once this type of data can easily be collected and is well accepted in the literature as a metric for inference of emotional states. Despite this popularity, due to several constraints found in real world scenarios (e.g. lightning, complex backgrounds, facial hair and so on), automatically obtaining affective information from face accurately is a very challenging accomplishment. This work presents a framework which aims to analyse emotional experiences through naturally generated facial expressions. Our main contribution is a new 4-dimensional model to describe emotional experiences in terms of appraisal, facial expressions, mood, and subjective experiences. In addition, we present an experiment using a new protocol proposed to obtain spontaneous emotional reactions. The results have suggested that the initial emotional state described by the participants of the experiment was different from that described after the exposure to the eliciting stimulus, thus showing that the used stimuli were capable of inducing the expected emotional states in most individuals. Moreover, our results pointed out that spontaneous facial reactions to emotions are very different from those in prototypic expressions due to the lack of expressiveness in the latter.

On Provable Algorithms for Determination of Continuous Protein Interdomain Motions from Residual Dipolar Couplings

Dynamics of biomolecules over various spatial and time scales are essential for biological functions such as molecular recognition, catalysis and signaling. However, reconstruction of biomolecular dynamics from experimental observables requires the determination of a conformational probability distribution. Unfortunately, these distributions cannot be fully constrained by the limited information from experiments, making the problem an ill-posed one in the terminology of Hadamard. The ill-posed nature of the problem comes from the fact that it has no unique solution. Multiple or even an infinite number of solutions may exist. To avoid the ill-posed nature, the problem needs to be regularized by making assumptions, which inevitably introduce biases into the result.

Here, I present two continuous probability density function approaches to solve an important inverse problem called the RDC trigonometric moment problem. By focusing on interdomain orientations we reduced the problem to determination of a distribution on the 3D rotational space from residual dipolar couplings (RDCs). We derived an analytical equation that relates alignment tensors of adjacent domains, which serves as the foundation of the two methods. In the first approach, the ill-posed nature of the problem was avoided by introducing a continuous distribution model, which enjoys a smoothness assumption. To find the optimal solution for the distribution, we also designed an efficient branch-and-bound algorithm that exploits the mathematical structure of the analytical solutions. The algorithm is guaranteed to find the distribution that best satisfies the analytical relationship. We observed good performance of the method when tested under various levels of experimental noise and when applied to two protein systems. The second approach avoids the use of any model by employing maximum entropy principles. This 'model-free' approach delivers the least biased result which presents our state of knowledge. In this approach, the solution is an exponential function of Lagrange multipliers. To determine the multipliers, a convex objective function is constructed. Consequently, the maximum entropy solution can be found easily by gradient descent methods. Both algorithms can be applied to biomolecular RDC data in general, including data from RNA and DNA molecules.

Multiple face detection at different resolutions for perceptual user interfaces

[EN]This paper describes in detail a real-time multiple face detection system for video streams. The system adds to the good performance provided by a window shift approach, the combination of different cues available in video streams due to temporal coherence. The results achieved by this combined solution outperform the basic face detector obtaining a 98% success rate for around 27000 images, providing additionally eye detection and a relation between the successive detections in time by means of detection threads.

Fast and robust face finding via local context

[EN]In visual surveillance face detection can be an important cue for initializing tracking algorithms. Recent work in psychophics hints at the importance of the local context of a face for robust detection, such as head contours and torso. This paper describes a detector that actively utilizes the idea of local context. The promise is to gain robustness that goes beyond the capabilities of traditional face detection making it particularly interesting for surveillance. The performance of the proposed detector in terms of accuracy and speed is evaluated on data sets from PETS 2000 and PETS 2003 and compared to the object-centered approach. Particular attention is paid to the role of available image resolution.

Ansiedade em face da morte em Agentes Funerários

Ao pensar na morte há um reconhecimento da vulnerabilidade humana e da própria fragilidade da vida. A morte é universal, mas experienciada de uma forma individualizada por cada um de nós, a partir da personalidade, experiências de vida, variáveis pessoais, idade, sexo, religião. Vivenciar a morte e o morrer poderá conduzir a sensações de medo e ansiedade. Os agentes funerários que lidam diariamente com a morte e com o “luto” (do corpo morto e dos familiares em relação ao ente querido que perderam) poderão estar expostos a sentimentos de ansiedade depressiva pela ativação diária do confronto com a própria morte, ou com a morte de pessoas a quem estão intimamente ligados. É objetivo deste estudo avaliar os níveis de ansiedade em face da morte em agentes funerários, e ainda explorar a eventual associação entre fatores sociodemográficos e profissionais selecionados e esta variável. A amostra é composta por 60 sujeitos de uma empresa funerária em Portugal. Os instrumentos psicométricos utilizados foram a Escala de Ansiedade face à Morte (DAQ), e um questionário sociodemográfico desenhado para o presente estudo. Os resultados globais mostram que os Agentes Funerários apresentam níveis de ansiedade face à morte estatisticamente significativos (M = 35,88; DP = 9,02). O género, a idade, religião, anos de experiência, estado civil, terem filhos, ter morrido alguém próximo ou significativo, especificidade de trabalho: ser comercial ou operacional o número de contatos, não marcam significativamente a forma como os sujeitos em estudo percecionam a sua ansiedade em face da morte. Os níveis de ansiedade aumentam entre aqueles que não tiveram formação específica para lidar com estas situações. / When thinking about death there is recognition of human vulnerability and fragility of life itself. Death is universal but experienced individually by each of us, through personality, life experiences, personal variables, age, sex, religion. Experiencing death and dying can lead to feelings of fear and anxiety. Funeral Agents who daily deal with death and with the "mourning" (the dead body and the family of the deceased) may be exposed to feelings of depressive anxiety activated by the daily confrontation with death itself or death of people who are close to them. The aim of this study is to assess the levels of anxiety in Funeral Agents when facing death, and also explore the eventual association of social-demographic and professional factors with this variable. The sample consisted of 60 subjects of a Portuguese Funeral company. The instruments used were the Death Anxiety Questionnaire (DAQ) and a socialdemographic questionnaire designed for the present study. The overall results show that Funeral Agents present anxiety levels statistically significant when facing death (M = 35.88, SD = 9.02). Gender, age, religion, years of experience, marital status, having children, the death of someone close or important, and the specificity of the job (commercial or operational agent), the number of contacts, show no statistically significant association with anxiety when facing death. However, the levels of anxiety increase among those who had had no specific formation to deal with these situations.

Patrocínio no circuito nacional de surf : estudo da notoriedade, atitude e intenção de compra dos espectadores face a uma marca

Com a realização deste estudo pretendeu-se cumprir dois objetivos: i) aferir a eficácia do patrocínio desportivo através da utilização de medidas como a notoriedade da marca, a atitude face ao patrocinador e a intenção de compra dos espectadores presentes no circuito nacional de surf (Liga Moche); ii) analisar a forma como o envolvimento das pessoas com o surf pode ter influência na eficácia do patrocínio. Para cumprir estes objetivos foram aplicados 250 questionários a espectadores presentes nas provas do circuito nacional de surf. Os dados foram analisados através de estatística descritiva, testes de correlação de Pearson e de tstudent. Os resultados indicam que a marca patrocinadora do evento de surf, a Moche, apresenta elevados níveis de notoriedade espontânea (83,2%) e assistida (91,2%) entre os espectadores do circuito nacional e que os espectadores apresentam também atitudes favoráveis assim como intenções de compra favoráveis. Verificou-se também uma correlação significativamente positiva entre a atitude face ao patrocinador e as intenções de compra. Por último, os praticantes de surf e os espectadores dos eventos apresentam uma atitude mais favorável e maiores intenções de compra dos produtos patrocinadores do que os que não praticam surf nem costumam assistir a eventos de surf. Estes resultados devem ser levados em consideração pelos responsáveis de futuros eventos de surf.

Object detection and recognition in complex scenes

Dissertação de Mestrado, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2014

Comparative study of human age estimation based on hand-crafted and deep face features

In the past few years, human facial age estimation has drawn a lot of attention in the computer vision and pattern recognition communities because of its important applications in age-based image retrieval, security control and surveillance, biomet- rics, human-computer interaction (HCI) and social robotics. In connection with these investigations, estimating the age of a person from the numerical analysis of his/her face image is a relatively new topic. Also, in problems such as Image Classification the Deep Neural Networks have given the best results in some areas including age estimation. In this work we use three hand-crafted features as well as five deep features that can be obtained from pre-trained deep convolutional neural networks. We do a comparative study of the obtained age estimation results with these features.

Incidencia de síndrome de abstinencia secundario a opioides y/o benzodiacepinas en dos unidades de cuidados intensivos pediátricos

• Introducción: El síndrome de abstinencia (SA) es el conjunto de síntomas y signos que se producen al suspender bruscamente la administración de un fármaco una vez se haya establecido dependencia física. • Objetivos: Caracterizar los pacientes que presentan SA secundario a opiodes (OP) y/o benzodiacepinas(BZ) durante la hospitalización en las unidades de cuidados intensivos pediátricos de la Clínica Infantil Colsubsidio (CIC) y Hospital del Niño de Panamá (HDN) del 1 de abril al 30 de septiembre del 2016. • Materiales y métodos: se realizó un estudio descriptivo, longitudinal, prospectivo. Incluimos 189 pacientes en la CIC y 144 pacientes en el HDN. Se utilizó la escala SOPHIA para el diagnóstico de SA, las escalas COMFORT para evaluar la sedación en pacientes ventilados no relajados y la escala FLACC para evaluar la analgesia. Se utilizó software StataV12® para el análisis estadístico. • Resultados: se reportó una incidencia global de SA de 6.1/100 días personas. La incidencia acumulada de SA fue de 56.08% y 29.86% para la CIC y el HDN respectivamente. En la CIC el 69.81% de los pacientes que requirieron infusión de OP y BZ desarrollaron SA. Se reportó una dosis acumulada de fentanyl de 530.34 ± 276.49 mcg/kg. Con respecto al HDN, de los pacientes que recibieron opioides y benzodiacepinas el 53.49 % desarrollaron SA. • Conclusión: El SA secundario a opioides y/o benzodiacepinas es frecuente en nuestras unidades con una incidencia variable, es mayor la presentación del SA al usar ambos fármacos, mayores dosis acumuladas y más días de infusión continua.

Improving Bangla ocr output through correction algorithms

Bangla OCR (Optical Character Recognition) is a long deserving software for Bengali community all over the world. Numerous e efforts suggest that due to the inherent complex nature of Bangla alphabet and its word formation process development of high fidelity OCR producing a reasonably acceptable output still remains a challenge. One possible way of improvement is by using post processing of OCR’s output; algorithms such as Edit Distance and the use of n-grams statistical information have been used to rectify misspelled words in language processing. This work presents the first known approach to use these algorithms to replace misrecognized words produced by Bangla OCR. The assessment is made on a set of fifty documents written in Bangla script and uses a dictionary of 541,167 words. The proposed correction model can correct several words lowering the recognition error rate by 2.87% and 3.18% for the character based n- gram and edit distance algorithms respectively. The developed system suggests a list of 5 (five) alternatives for a misspelled word. It is found that in 33.82% cases, the correct word is the topmost suggestion of 5 words list for n-gram algorithm while using Edit distance algorithm the first word in the suggestion properly matches 36.31% of the cases. This work will ignite rooms of thoughts for possible improvements in character recognition endeavour.

Test vector generation for the phase II ATLAS event filter trigger upgrade

In the near future, the LHC experiments will continue to be upgraded as the LHC luminosity will increase from the design 1034 to 7.5 × 1034, with the HL-LHC project, to reach 3000 × f b−1 of accumulated statistics. After the end of a period of data collection, CERN will face a long shutdown to improve overall performance by upgrading the experiments and implementing more advanced technologies and infrastructures. In particular, ATLAS will upgrade parts of the detector, the trigger, and the data acquisition system. It will also implement new strategies and algorithms for processing and transferring the data to the final storage. This PhD thesis presents a study of a new pattern recognition algorithm to be used in the trigger system, which is a software designed to provide the information necessary to select physical events from background data. The idea is to use the well-known Hough Transform mathematical formula as an algorithm for detecting particle trajectories. The effectiveness of the algorithm has already been validated in the past, independently of particle physics applications, to detect generic shapes in images. Here, a software emulation tool is proposed for the hardware implementation of the Hough Transform, to reconstruct the tracks in the ATLAS Trigger and Data Acquisition system. Until now, it has never been implemented on electronics in particle physics experiments, and as a hardware implementation it would provide overall latency benefits. A comparison between the simulated data and the physical system was performed on a Xilinx UltraScale+ FPGA device.

Governing algorithms in the big data era for balancing new digital rights - designing GDPR compliant and trustworthy XAI systems

This thesis investigates the legal, ethical, technical, and psychological issues of general data processing and artificial intelligence practices and the explainability of AI systems. It consists of two main parts. In the initial section, we provide a comprehensive overview of the big data processing ecosystem and the main challenges we face today. We then evaluate the GDPR’s data privacy framework in the European Union. The Trustworthy AI Framework proposed by the EU’s High-Level Expert Group on AI (AI HLEG) is examined in detail. The ethical principles for the foundation and realization of Trustworthy AI are analyzed along with the assessment list prepared by the AI HLEG. Then, we list the main big data challenges the European researchers and institutions identified and provide a literature review on the technical and organizational measures to address these challenges. A quantitative analysis is conducted on the identified big data challenges and the measures to address them, which leads to practical recommendations for better data processing and AI practices in the EU. In the subsequent part, we concentrate on the explainability of AI systems. We clarify the terminology and list the goals aimed at the explainability of AI systems. We identify the reasons for the explainability-accuracy trade-off and how we can address it. We conduct a comparative cognitive analysis between human reasoning and machine-generated explanations with the aim of understanding how explainable AI can contribute to human reasoning. We then focus on the technical and legal responses to remedy the explainability problem. In this part, GDPR’s right to explanation framework and safeguards are analyzed in-depth with their contribution to the realization of Trustworthy AI. Then, we analyze the explanation techniques applicable at different stages of machine learning and propose several recommendations in chronological order to develop GDPR-compliant and Trustworthy XAI systems.

Antibody Recognition Of Plasmodium Falciparum Infected Red Blood Cells By Symptomatic And Asymptomatic Individuals In The Brazilian Amazon.

In the Amazon Region, there is a virtual absence of severe malaria and few fatal cases of naturally occurring Plasmodium falciparum infections; this presents an intriguing and underexplored area of research. In addition to the rapid access of infected persons to effective treatment, one cause of this phenomenon might be the recognition of cytoadherent variant proteins on the infected red blood cell (IRBC) surface, including the var gene encoded P. falciparum erythrocyte membrane protein 1. In order to establish a link between cytoadherence, IRBC surface antibody recognition and the presence or absence of malaria symptoms, we phenotype-selected four Amazonian P. falciparum isolates and the laboratory strain 3D7 for their cytoadherence to CD36 and ICAM1 expressed on CHO cells. We then mapped the dominantly expressed var transcripts and tested whether antibodies from symptomatic or asymptomatic infections showed a differential recognition of the IRBC surface. As controls, the 3D7 lineages expressing severe disease-associated phenotypes were used. We showed that there was no profound difference between the frequency and intensity of antibody recognition of the IRBC-exposed P. falciparum proteins in symptomatic vs. asymptomatic infections. The 3D7 lineages, which expressed severe malaria-associated phenotypes, were strongly recognised by most, but not all plasmas, meaning that the recognition of these phenotypes is frequent in asymptomatic carriers, but is not necessarily a prerequisite to staying free of symptoms.

Biased Random-key Genetic Algorithms For The Winner Determination Problem In Combinatorial Auctions.

Abstract In this paper, we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer-linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.