Intelligent line segment perception with cortex-like mechanisms

This paper proposes a novel general framework for line segment perception, which is motivated by a biological visual cortex, and requires no parameter tuning. In this framework, we design a model to approximate receptive fields of simple cells. More importantly, the structure of biological orientation columns is imitated by organizing artificial complex and hypercomplex cells with the same orientation into independent arrays. Besides, an interaction mechanism is implemented by a set of self-organization rules. Enlightened by the visual topological theory, the outputs of these artificial cells are integrated to generate line segments that can describe nonlocal structural information of images. Each line segment is evaluated quantitatively by its significance. The computation complexity is also analyzed. The proposed method is tested and compared to state-of-the-art algorithms on real images with complex scenes and strong noises. The experiments demonstrate that our method outperforms the existing methods in the balance between conciseness and completeness.

Teorias em estratégia

A estratégia empresarial é uma disciplina jovem. Comparado com os campos de estudo de economia e sociologia o campo de estratégia empresarial pode ser visto como um fenômeno de formação mais recente, embora extremamente dinâmico em sua capacidade de criar abordagens teóricas diferenciadas. Este trabalho discute a recente proliferação de teorias em estratégia empresarial, propondo um modelo de classificação destas teorias baseado na análise empírica do modelo de escolas de pensamento em estratégia empresarial desenvolvido por Mintzberg, Ahlstrand e Lampel em seu livro Safári de Estratégia (1998). As possíveis conseqüências relativas à interação entre teoria e prática são também discutidas apresentando o que definimos como a síndrome do ornitorrinco.

Ensaio sobre o agente racional: esparadrapos para um paciente terminal?

The Rational Agent model have been a foundational basis for theoretical models such as Economics, Management Science, Artificial Intelligence and Game Theory, mainly by the ¿maximization under constraints¿ principle, e.g. the ¿Expected Utility Models¿, among them, the Subjective Expected Utility (SEU) Theory, from Savage, placed as most influence player over theoretical models we¿ve seen nowadays, even though many other developments have been done, indeed also in non-expected utility theories field. Having the ¿full rationality¿ assumption, going for a less idealistic sight ¿bounded rationality¿ of Simon, or for classical anomalies studies, such as the ¿heuristics and bias¿ analysis by Kahneman e Tversky, ¿Prospect Theory¿ also by Kahneman & Tversky, or Thaler¿s Anomalies, and many others, what we can see now is that Rational Agent Model is a ¿Management by Exceptions¿ example, as for each new anomalies¿s presentation, in sequence, a ¿problem solving¿ development is needed. This work is a theoretical essay, which tries to understand: 1) The rational model as a ¿set of exceptions¿; 2) The actual situation unfeasibility, since once an anomalie is identified, we need it¿s specific solution developed, and since the number of anomalies increases every year, making strongly difficult to manage rational model; 3) That behaviors judged as ¿irrationals¿ or deviated, by the Rational Model, are truly not; 4) That¿s the right moment to emerge a Theory including mental processes used in decision making; and 5) The presentation of an alternative model, based on some cognitive and experimental psychology analysis, such as conscious and uncounscious processes, cognition, intuition, analogy-making, abstract roles, and others. Finally, we present conclusions and future research, that claims for deeper studies in this work¿s themes, for mathematical modelling, and studies about a rational analysis and cognitive models possible integration. .

A multi-method approach for the assessment of composite indices and rankings

There is growing popularity in the use of composite indices and rankings for cross-organizational benchmarking. However, little attention has been paid to alternative methods and procedures for the computation of these indices and how the use of such methods may impact the resulting indices and rankings. This dissertation developed an approach for assessing composite indices and rankings based on the integration of a number of methods for aggregation, data transformation and attribute weighting involved in their computation. The integrated model developed is based on the simulation of composite indices using methods and procedures proposed in the area of multi-criteria decision making (MCDM) and knowledge discovery in databases (KDD). The approach developed in this dissertation was automated through an IT artifact that was designed, developed and evaluated based on the framework and guidelines of the design science paradigm of information systems research. This artifact dynamically generates multiple versions of indices and rankings by considering different methodological scenarios according to user specified parameters. The computerized implementation was done in Visual Basic for Excel 2007. Using different performance measures, the artifact produces a number of excel outputs for the comparison and assessment of the indices and rankings. In order to evaluate the efficacy of the artifact and its underlying approach, a full empirical analysis was conducted using the World Bank's Doing Business database for the year 2010, which includes ten sub-indices (each corresponding to different areas of the business environment and regulation) for 183 countries. The output results, which were obtained using 115 methodological scenarios for the assessment of this index and its ten sub-indices, indicated that the variability of the component indicators considered in each case influenced the sensitivity of the rankings to the methodological choices. Overall, the results of our multi-method assessment were consistent with the World Bank rankings except in cases where the indices involved cost indicators measured in per capita income which yielded more sensitive results. Low income level countries exhibited more sensitivity in their rankings and less agreement between the benchmark rankings and our multi-method based rankings than higher income country groups.

Del videojuego a la realidad : sistema interactivo para la seguridad vial

El vertiginoso crecimiento de los centros urbanos, las tecnologías emergentes y la demanda de nuevos servicios por parte de la población plantea encaminar esfuerzos hacia el desarrollo de las ciudades inteligentes. Éste concepto ha tomado fuerza entre los sectores político, económico, social, académico, ambiental y civil; de forma paralela, se han generado iniciativas que conducen hacia la integración de la infraestructura, la tecnología y los servicios para los ciudadanos. En éste contexto, una de las problemáticas con mayor impacto en la sociedad es la seguridad vial. Es necesario contar con mecanismos que disminuyan la accidentalidad, mejoren la atención a incidentes, optimicen la movilidad urbana y planeación municipal, ayuden a reducir el consumo de combustible y la emisión de gases de efecto de invernadero, así como ofrecer información dinámica y efectiva a los viajeros. En este artículo se describen dos (2) enfoques que contribuyen de manera eficiente dicho problema: los videojuegos como juegos serios y los sistemas de transporte inteligente. Ambos enfoques están encaminados a evitar colisiones y su diseño e implementación requieren componentes altamente tecnológicos (e.g. sistemas telemáticos e informáticos, inteligencia artificial, procesamiento de imágenes y modelado 3D).

Turning gaming EEG peripherals into trainable brain computer interfaces

Companies such as NeuroSky and Emotiv Systems are selling non-medical EEG devices for human computer interaction. These devices are significantly more affordable than their medical counterparts, and are mainly used to measure levels of engagement, focus, relaxation and stress. This information is sought after for marketing research and games. However, these EEG devices have the potential to enable users to interact with their surrounding environment using thoughts only, without activating any muscles. In this paper, we present preliminary results that demonstrate that despite reduced voltage and time sensitivity compared to medical-grade EEG systems, the quality of the signals of the Emotiv EPOC neuroheadset is sufficiently good in allowing discrimina tion between imaging events. We collected streams of EEG raw data and trained different types of classifiers to discriminate between three states (rest and two imaging events). We achieved a generalisation error of less than 2% for two types of non-linear classifiers.

Natural versus artificial scene classification by ordering discrete fourier power spectra

Holistic representations of natural scenes is an effective and powerful source of information for semantic classification and analysis of arbitrary images. Recently, the frequency domain has been successfully exploited to holistically encode the content of natural scenes in order to obtain a robust representation for scene classification. In this paper, we present a new approach to naturalness classification of scenes using frequency domain. The proposed method is based on the ordering of the Discrete Fourier Power Spectra. Features extracted from this ordering are shown sufficient to build a robust holistic representation for Natural vs. Artificial scene classification. Experiments show that the proposed frequency domain method matches the accuracy of other state-of-the-art solutions. © 2008 Springer Berlin Heidelberg.

Product intelligence in warehouse management: A case study

The need for more flexible, adaptable and customer-oriented warehouse operations has been increasingly identified as an important issue by today's warehouse companies due to the rapidly changing preferences of the customers that use their services. Motivated by manufacturing and other logistics operations, in this paper we argue on the potential application of product intelligence in warehouse operations as an approach that can help warehouse companies address these issues. We discuss the opportunities of such an approach using a real example of a third-party-logistics warehouse company and we present the benefits it can bring in their warehouse management systems. © 2013 Springer-Verlag.

The Influence of Epistemology on the Design of Artificial Agents

Lee, M. H., Lacey, N. J. (2003). The Influence of Epistemology on the Design of Artificial Agents. Minds and Machines, 13 (3), 367-395

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.

Artificial Neural Network for Compositional Ionic Liquid Viscosity Prediction

Being a new generation of green solvents and high-tech reaction media of the future, ionic liquids have increasingly attracted much attention. Of particular interest in this context are room temperature ionic liquids (in short as ILs in this paper). Due to the relatively high viscosity, ILs is expected to be used in the form of solvent diluted mixture with reduced viscosity in industrial application, where predicting the viscosity of IL mixture has been an important research issue. Different IL mixture and many modelling approaches have been investigated. The objective of this study is to provide an alternative model approach using soft computing technique, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of ILs [C _n-mim][NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0-328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity taking account of IL alkyl chain length, as well as temperature and compositions simultaneously, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. This illustrates the potential application of ANN in the case that the physical and thermodynamic properties are highly non-linear or too complex. © 2012 Copyright the authors.

Introdução à inteligência artificial com recurso à programação visual

Relatório da Prática de Ensino Supervisionada, Mestrado em Ensino da Matemática, Universidade de Lisboa, Instituto de Educação, 2014

Application of computational intelligence to engineering

Computational Intelligence (CI) includes four main areas: Evolutionary Computation (genetic algorithms and genetic programming), Swarm Intelligence, Fuzzy Systems and Neural Networks. This article shows how CI techniques overpass the strict limits of Artificial Intelligence field and can help solving real problems from distinct engineering areas: Mechanical, Computer Science and Electrical Engineering.