Coleção de Artigos Acadêmicos
URI permanente para esta coleçãohttps://repositorio.insper.edu.br/handle/11224/3227
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Artigo Científico Direitos Humanos, inteligência artificial e privacidade(2019) Cassino, João Francisco; RODOLFO DA SILVA AVELINO; Silveira, Sérgio Amadeu daEste texto trata dos riscos e implicações da inteligência artificial e dos algoritmos para os objetivos contidos na Declaração Universal dos Direitos Humanos. Nesse sentido, as perspectivas de James Der Derian, Frank Pasquale, David Chandler, Shoshana Zuboff, Philip N. Howard e Nick Srnicek foram mobilizadas para a compreensão da atual fase do capitalismo global, do mercado de captura e o processamento em massa de dados pessoais. Diversos casos descritos indicam que a privacidade é cada vez menos respeitada enquanto as empresas protegem seus segredos competitivos com patentes, códigos fechados e acordos de confidencialidade. Técnicas de Big Data e algoritmos em rede podem ser utilizados para melhorar e agilizar a administração pública, mas também resultam em novas práticas discriminatórias que violam o direito à privacidade, à liberdade de expressão e à justiça. Grupos étnicos e raciais, mulheres e comunidade LGBT já sofrem com decisões tomadas por sistemas computacionais autômatos que levam à segregação e ao preconceito.Artigo Científico SNA-Based Reasoning for Multi-Agent Team Composition(2015) ANDRE FILIPE DE MORAES BATISTA; Marietto, Maria das Graças BrunoThe social network analysis (SNA), branch of complex systems can be used in the construction of multi agent systems. This paper proposes a study of how social network analysis can assist in modeling multi agent systems, while addressing similarities and differences between the two theories. We built a prototype of multi-agent systems for resolution of tasks through the formation of teams of agents that are formed on the basis of the social network established between agents. Agents make use of performance indicators to assess when should change their social network to maximize the participation in teams.Artigo Científico Uma introdução ao tema Recuperação de Informações Textuais(2013) FABRÍCIO JAILSON BARTHO tema Recuperação de Informação sempre foi um tema muito explorado na academia e no mercado. A forma com que os eventos acadêmicos são conduzidos demonstra uma maturidade muito grande da área, inclusive com uma ligação muito forte com o mercado. Inúmeros livros sobre este tema já foram publicados. No entanto, são poucos os livros publicados em português. Este tutorial tenta preencher esta lacuna apresentando uma introdução sobre o tema Recuperação de Informação, abordando: as principais definições e conceitos da área; os principais modelos que regem o desenvolvimento dos Sistemas de Recuperação de Informação, e; os métodos usualmente empregados na avaliação de Sistemas de Recuperação de Informação.Artigo Científico Pollution, bad-mouthing, and local marketing: The underground of location-based social networks(2014) Costa, Helen; Merschmann, Luiz H.C.; FABRÍCIO JAILSON BARTH; Benevenuto, FabrícioLocation Based Social Networks (LBSNs) are new Web 2.0 systems that are attracting new users in exponential rates. LBSNs like Foursquare and Yelp allow users to share their geographic location with friends through smartphones equipped with GPS, search for interesting places as well as posting tips about existing locations. By allowing users to comment on locations, LBSNs increasingly have to deal with new forms of spammers, which aim at advertising unsolicited messages on tips about locations. Spammers may jeopardize the trust of users on the system, thus, compromising its success in promoting location-based social interactions. In spite of that, the available literature is very limited in providing a deep understanding of this problem. In this paper, we investigated the task of identifying different types of tip spam on a popular Brazilian LBSN system, namely Apontador. Based on a labeled collection of tips provided by Apontador as well as crawled information about users and locations, we identified three types of irregular tips, namely local marketing, pollution and, bad-mouthing. We leveraged our characterization study towards a classification approach able to differentiate these tips with high accuracy.Artigo Científico An investigation of the distribution of gaze estimation errors in head mounted gaze trackers using polynomial functions(2018) Mardanbegi, Diako; ANDREW TOSHIAKI NAKAYAMA KURAUCHI; Morimoto, Carlos H.Second order polynomials are commonly used for estimating the point-of-gaze in head-mounted eye trackers. Studies in remote (desktop) eye trackers show that although some non-standard 3rd order polynomial models could provide better accuracy, high-order polynomials do not necessarily provide better results. Different than remote setups though, where gaze is estimated over a relatively narrow field-of-view surface (e.g. less than 30x20 degrees on typical computer displays), head-mounted gaze trackers (HMGT) are often desired to cover a relatively wider field-of-view to make sure that the gaze is detected in the scene image even for extreme eye angles. In this paper we investigate the behavior of the gaze estimation error distribution throughout the image of the scene camera when using polynomial functions. Using simulated scenarios, we describe effects of four different sources of error: interpolation, extrapolation, parallax, and radial distortion. We show that the use of third order polynomials result in more accurate gaze estimates in HMGT, and that the use of wide angle lenses might be beneficial in terms of error reduction.Artigo Científico Correlation between graphs with an application to brain network analysis(2017) Fujita, André; Takahashi, Daniel Yasumasa; Balardin, Joana Bisol; MACIEL CALEBE VIDAL; Sato, João RicardoThe global functional brain network (graph) is more suitable for characterizing brain states than local analysis of the connectivity of brain regions. Therefore, graph-theoretic approaches are natural methods to use for studying the brain. However, conventional graph theoretical analyses are limited due to the lack of formal statistical methods of estimation and inference. For example, the concept of correlation between two vectors of graphs has not yet been defined. Thus, the introduction of a notion of correlation between graphs becomes necessary to better understand how brain sub-networks interact. To develop a framework to infer correlation between graphs, one may assume that they are generated by models and that the parameters of the models are the random variables. Then, it is possible to define that two graphs are independent when the random variables representing their parameters are independent. In the real world, however, the model is rarely known, and consequently, the parameters cannot be estimated. By analyzing the graph spectrum, it is shown that the spectral radius is highly associated with the parameters of the graph model. Based on this, a framework for correlation inference between graphs is constructed and the approach illustrated on functional magnetic resonance imaging data on 814 subjects comprising 529 controls and 285 individuals diagnosed with autism spectrum disorder (ASD). Results show that correlations between the default-mode and control, default-mode and somatomotor, and default-mode and visual sub-networks are higher in individuals with ASD than in the controls.Artigo Científico A Software to Compare Clusters between Groups and Its Application to the Study of Autism Spectrum Disorder(2017) MACIEL CALEBE VIDAL; Sato, João R.; Balardin, Joana B.; Takahashi, Daniel Y.; Fujita, AndréUnderstanding how brain activities cluster can help in the diagnosis of neuropsychological disorders. Thus, it is important to be able to identify alterations in the clustering structure of functional brain networks. Here, we provide an R implementation of Analysis of Cluster Variability (ANOCVA), which statistically tests (1) whether a set of brain regions of interest (ROI) are equally clustered between two or more populations and (2) whether the contribution of each ROI to the differences in clustering is significant. To illustrate the usefulness of our method and software, we apply the R package in a large functional magnetic resonance imaging (fMRI) dataset composed of 896 individuals (529 controls and 285 diagnosed with ASD—autism spectrum disorder) collected by the ABIDE (The Autism Brain Imaging Data Exchange) Consortium. Our analysis show that the clustering structure of controls and ASD subjects are different (p < 0.001) and that specific brain regions distributed in the frontotemporal, sensorimotor, visual, cerebellar, and brainstem systems significantly contributed (p < 0.05) to this differential clustering. These findings suggest an atypical organization of domain-specific functionbrain modules in ASD.Artigo Científico Identification of alterations associated with age in the clustering structure of functional brain networks(2018) Guzman, Grover E. C.; Sato, Joao R.; MACIEL CALEBE VIDAL; Fujita, AndreInitial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals’ functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.Artigo Científico Estimation of the tissue composition of the tumour mass in neuroblastoma using segmented CT images(2004) FABIO JOSE AYRES; M. K. Zuffo,; Rangayyan, R. M.; Boag, G. S.; O. Filho, V.; Valente , M.Neuroblastoma is the most common extra-cranial, solid, malignant tumour in children. Advances in radiology have made possible the detection and staging of the disease. Nevertheless, there is no method available at present that can go beyond detection and qualitative analysis, towards quantitative assessment of the tissues composition of the primary tumour mass in neuroblastoma. Such quantitative analysis could provide important information and serve as a decision-support tool to the radiologist and the oncologist, result in better treatment and follow-up and even lead to the avoidance of delayed surgery. The problem investigated was the improvement of the analysis of the primary tumour mass, in patients with neuroblastoma, using X-ray computed tomography (CT) images. A methodology was proposed for the estimation of the tissue content of the mass: it comprised a Gaussian mixture model for estimation, from segmented CT images, of the tissue composition of the primary tumour. To demonstrate the potential of the method, the results are presented of its application to ten CT examinations of four patients. The method provides quantitative information, and it was observed that the tumour in one of the patients reduced from 523 cm3 to 81 cm3 in volume, with an increase in calcification from about 20% to about 88% of the tumour volume, in response to chemotherapy over a period of five months. Results indicate that the proposed technique may be of considerable value in assessing the response to therapy of patients with neuroblastoma.Artigo Científico Gabor filters and phase portraits for the detection of architectural distortion in mammograms(2006) Rangayyan, Rangaraj M.; FABIO JOSE AYRESSegmentation of the tumor in neuroblastoma is complicated by the fact that the mass is almost Always heterogeneous in nature; furthermore, viable Architectural distortion is a subtle abnormality in mammograms, and a source of overlooking errors by radiologists. Computer-aided diagnosis (CAD) techniques can improve the performance of radiologists in detecting masses and calcifications; however, most CAD systems have not been designed to detect architectural distortion. We present a new method to detect and localise architectural distortion by analysing the oriented texture in mammograms. A bank of Gabor filters is used to obtain the orientation field of the given mammogram. The curvilinear structures (CLS) of interest (spicules and fibrous tissue) are separated from confounding structures (pectoral muscle edge, parenchymal tissue edges, breast boundary, and noise). The selected core CLS pixels and the orientation field are filtered and downsampled, to reduce noise and also to reduce the computational effort required by the subsequent methods. The downsampled orientation field is analysed to produce three phase portrait maps: node, saddle, and spiral. The node map is further analysed in order to detect the sites of architectural distortion. The method was tested with 19 mammograms containing architectural distortion. In a preliminary experiment, a sensitivity of 84% was obtained at 7.8 false positives per image.