Interaction and Intelligent Behavior

We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Rapid estimation of cartilage T2 based on double echo at steady state (DESS) with 3 Tesla

The double-echo-steady-state (DESS) sequence generates two signal echoes that are characterized by a different contrast behavior. Based on these two contrasts, the underlying T2 can be calculated. For a flip-angle of 90 degrees , the calculated T2 becomes independent of T1, but with very low signal-to-noise ratio. In the present study, the estimation of cartilage T2, based on DESS with a reduced flip-angle, was investigated, with the goal of optimizing SNR, and simultaneously minimizing the error in T2. This approach was validated in phantoms and on volunteers. T2 estimations based on DESS at different flip-angles were compared with standard multiecho, spin-echo T2. Furthermore, DESS-T2 estimations were used in a volunteer and in an initial study on patients after cartilage repair of the knee. A flip-angle of 33 degrees was the best compromise for the combination of DESS-T2 mapping and morphological imaging. For this flip angle, the Pearson correlation was 0.993 in the phantom study (approximately 20% relative difference between SE-T2 and DESS-T2); and varied between 0.429 and 0.514 in the volunteer study. Measurements in patients showed comparable results for both techniques with regard to zonal assessment. This DESS-T2 approach represents an opportunity to combine morphological and quantitative cartilage MRI in a rapid one-step examination.

Ethnic comparisons of adolescent sexual risk -taking and preventive behavior

For adolescents, unprotected sexual intercourse is the primary cause of sexually transmitted disease (STD), including Human Immunodeficiency Virus (HIV) infection (virus which causes Acquired Immunodeficiency Syndrome (AIDS)), and pregnancy. Although many studies on adolescent sexual behavior have addressed racial/ethnic differences, few studies have examined the relation between race/ethnicity while controlling for other sociocultural and psychosocial variables. The purpose of this study is to examine the relationship between racial/ethnic categories and selected sociocultural and psychosocial variables, with reported adolescent sexual risk-taking and preventive behavior.^ A self-administered questionnaire was used to collect information from 3132 students in a Texas school district (Section 3.5.2). The instrument contained approximately 100 questions on demographic characteristics, sexual behavior, and psychosocial determinants of sexual behavior. Based on the findings of this study, the following major conclusions are made: (1) There are differences in reported sexual risk-taking and preventive behavior among Black, Hispanic and White adolescents in this study. The stratified analysis by gender further suggests significant gender differences in reported sexual behavior among the three racial/ethnic groups. (2) Gender, living arrangement, academic grades, and language spoken at home modified the association between reported sexual risk-taking and preventive behavior and race/ethnicity in this study. This suggests that these sociocultural variables should be considered in future research and practice involving multicultural populations. (3) There are differences in selected psychosocial determinants among the three racial/ethnic groups and between males and females. These differences were consistent with the reported sexual risk-taking and preventive behaviors among race/ethnicity and gender for adolescents in this study. The findings support the consideration of psychosocial determinants in research and interventions addressing adolescent sexual behavior among different racial/ethnic groups.^ Based on the results of this study, two recommendations for practice are made. First, health professionals developing interventions for adolescents from different cultural backgrounds and gender need to be familiar with the specific sociocultural and psychosocial factors which will reduce risky sexual behavior, and promote protective behavior. Second, the need for immediate, realistic, and continuous HIV/STD and pregnancy prevention programs for children and adolescents should be considered. ^

Self-organized defensive behavior in honeybees

We investigated the defensive behavior of honeybees under controlled experimental conditions. During an attack on two identical targets, the spatial distribution of stings varied as a function of the total number of stings, evincing the classic “pitchfork bifurcation” phenomenon of nonlinear dynamics. The experimental results support a model of defensive behavior based on a self-organizing mechanism. The model helps to explain several of the characteristic features of the honeybee defensive response: (i) the ability of the colony to localize and focus its attack, (ii) the strong variability between different hives in the intensity of attack, as well as (iii) the variability observed within the same hive, and (iv) the ability of the colony to amplify small differences between the targets.

Fuzzy logic-based implicit authentication for mobile access control

In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.

User Behavioral Modeling of Web-based Systems for Continuous User Authentication

Authentication plays an important role in how we interact with computers, mobile devices, the web, etc. The idea of authentication is to uniquely identify a user before granting access to system privileges. For example, in recent years more corporate information and applications have been accessible via the Internet and Intranet. Many employees are working from remote locations and need access to secure corporate files. During this time, it is possible for malicious or unauthorized users to gain access to the system. For this reason, it is logical to have some mechanism in place to detect whether the logged-in user is the same user in control of the user's session. Therefore, highly secure authentication methods must be used. We posit that each of us is unique in our use of computer systems. It is this uniqueness that is leveraged to "continuously authenticate users" while they use web software. To monitor user behavior, n-gram models are used to capture user interactions with web-based software. This statistical language model essentially captures sequences and sub-sequences of user actions, their orderings, and temporal relationships that make them unique by providing a model of how each user typically behaves. Users are then continuously monitored during software operations. Large deviations from "normal behavior" can possibly indicate malicious or unintended behavior. This approach is implemented in a system called Intruder Detector (ID) that models user actions as embodied in web logs generated in response to a user's actions. User identification through web logs is cost-effective and non-intrusive. We perform experiments on a large fielded system with web logs of approximately 4000 users. For these experiments, we use two classification techniques; binary and multi-class classification. We evaluate model-specific differences of user behavior based on coarse-grain (i.e., role) and fine-grain (i.e., individual) analysis. A specific set of metrics are used to provide valuable insight into how each model performs. Intruder Detector achieves accurate results when identifying legitimate users and user types. This tool is also able to detect outliers in role-based user behavior with optimal performance. In addition to web applications, this continuous monitoring technique can be used with other user-based systems such as mobile devices and the analysis of network traffic.

Effects of bromazepam in frontal theta activity on the performance of a sensorimotor integration task: A quantitative electroencephalography study

Our objective is to verify the modulatory effects of bromazepam on EEG theta absolute power when subjects were submitted to a visuomotor task (i.e., car driver task). Sample was composed of 14 students (9 males and 5 females), right handed, with ages varying between 23 and 42 years (mean = 32.5 +/- 9.5), absence of mental or physical impairments, no psychoactive or psychotropic substance use and no neuromuscular disorders (screened by a clinical examination). The results showed an interaction between condition and electrodes (p=0.034) in favor of F8 electrode compared with F7 in both experimental conditions (t-test; p=0.001). Additionally, main effects were observed for condition (p=0.001), period (p=0.001) and electrodes (p=0.031) in favor of F4 electrode compared with F3. In conclusion, Br 6 mg of bromazepam may interfere in sensorimotor processes in the task performance in an unpredictable scenario allowing that certain visuospatial factors were predominant. Therefore, the results may reflect that bromazepam effects influence the performance of the involved areas because of the acquisition and integration of sensory stimuli processes until the development of a motor behavior based on the same stimuli. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Verificação da segurança sísmica de um edifício existente em betão armado

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

Análise do comportamento de estruturas através de ensaios de carga

A engenharia civil, rege-se pela garantia de segurança e de funcionalidade das obras que projeta e executa. Para cumprir tais requisitos, é necessário durante a sua vida útil, no final da construção, reforço ou reabilitação, proceder à avaliação da conformidade entre o comportamento real da estrutura e os pressupostos subjacentes ao projeto. Esta dissertação tem como objetivo a compreensão e análise do comportamento estrutural da Ponte sobre o Rio Sorraia, através da realização de ensaios de carga apoiados pela conceção de um modelo numérico devidamente calibrado, capaz de simular a resposta da estrutura, o mais próximo possível do observável na realidade. Para alcançar o objetivo pré definido elencam-se as metodologias relevantes, descrevem-se os tipos de ensaios de carga realizados em pontes/viadutos e faz-se referência aos aparelhos de medição que estão na base da instrumentação aplicada em obras. Esta introdução foca-se ainda na modelação numérica, permitindo o conhecimento básico necessário para a criação e atualização de modelos numéricos de pontes. Relativamente ao caso de estudo expõe-se a realização do ensaio de carga, descrevendo todo o processo, bem como os resultados obtidos ao nível das grandezas de medição estudadas. Aqui é concebido um modelo numérico base da ponte, alvo de discussão ao nível do comportamento estrutural, baseada na validação dos resultados obtidos por via experimental, através da comparação com os obtidos por via numérica. Por fim, o estudo e seleção de diversos parâmetros da modelação, facultando a calibração do modelo numérico da ponte. Os resultados obtidos neste modelo comprovam o seu elevado potencial, no apoio à observação e compreensão do comportamento de estruturas através da realização de ensaios de carga. O sucesso da realização de uma análise do comportamento de estruturas, através de ensaios de carga, depende assim fundamentalmente, da correta execução do ensaio, da correta conceção e atualização do modelo numérico e da interligação entre os resultados experimentais e numéricos.

Internationalization strategies and methods of construction firms – a comparative study between Hong Kong - Chinese and Portuguese – European approaches

Dissertação para obtenção do Grau Mestre em Engenharia Civil – Perfil de Construção

Service offshoring and white-collar employment

This paper empirically studies the effects of service offshoring on white-collar employment, using data for more than one hundred U.S. occupations. A model of firm behavior based on separability allows to derive the labor demand elasticity with respect to service offshoring for each occupation. Estimation is performed with Quasi-Maximum Likelihood, to account for high degrees of censoring in the employment variable. The estimated elasticities are then related to proxies for the skill level and the degree of tradability of the occupations. Results show that service offshoring increases high skilled employment and decreases medium and low skilled employment. Within each skill group, however, service offshoring penalizes tradable occupations and benefits non-tradable occupations.

A behavioral ecology of shermen: hidden stories from trajectory data in the Northern Humboldt Current System

This work proposes an original contribution to the understanding of shermen spatial behavior, based on the behavioral ecology and movement ecology paradigms. Through the analysis of Vessel Monitoring System (VMS) data, we characterized the spatial behavior of Peruvian anchovy shermen at di erent scales: (1) the behavioral modes within shing trips (i.e., searching, shing and cruising); (2) the behavioral patterns among shing trips; (3) the behavioral patterns by shing season conditioned by ecosystem scenarios; and (4) the computation of maps of anchovy presence proxy from the spatial patterns of behavioral mode positions. At the rst scale considered, we compared several Markovian (hidden Markov and semi-Markov models) and discriminative models (random forests, support vector machines and arti cial neural networks) for inferring the behavioral modes associated with VMS tracks. The models were trained under a supervised setting and validated using tracks for which behavioral modes were known (from on-board observers records). Hidden semi-Markov models performed better, and were retained for inferring the behavioral modes on the entire VMS dataset. At the second scale considered, each shing trip was characterized by several features, including the time spent within each behavioral mode. Using a clustering analysis, shing trip patterns were classi ed into groups associated to management zones, eet segments and skippers' personalities. At the third scale considered, we analyzed how ecological conditions shaped shermen behavior. By means of co-inertia analyses, we found signi cant associations between shermen, anchovy and environmental spatial dynamics, and shermen behavioral responses were characterized according to contrasted environmental scenarios. At the fourth scale considered, we investigated whether the spatial behavior of shermen re ected to some extent the spatial distribution of anchovy. Finally, this work provides a wider view of shermen behavior: shermen are not only economic agents, but they are also foragers, constrained by ecosystem variability. To conclude, we discuss how these ndings may be of importance for sheries management, collective behavior analyses and end-to-end models.