1,311 research outputs found
Deep learning model combination and regularization using convolutional neural networks
Convolutional neural networks (CNNs) were inspired by biology. They are hierarchical neural
networks whose convolutional layers alternate with subsampling layers, reminiscent of simple
and complex cells in the primary visual cortex [Fuk86a]. In the last years, CNNs have emerged
as a powerful machine learning model and achieved the best results in many object recognition
benchmarks [ZF13, HSK+12, LCY14, CMMS12].
In this dissertation, we introduce two new proposals for convolutional neural networks. The
first, is a method to combine the output probabilities of CNNs which we call Weighted
Convolutional Neural Network Ensemble. Each network has an associated weight that makes
networks with better performance have a greater influence at the time to classify a pattern
when compared to networks that performed worse. This new approach produces better results
than the common method that combines the networks doing just the average of the output
probabilities to make the predictions. The second, which we call DropAll, is a generalization
of two well-known methods for regularization of fully-connected layers within convolutional
neural networks, DropOut [HSK+12] and DropConnect [WZZ+13]. Applying these methods
amounts to sub-sampling a neural network by dropping units. When training with DropOut, a
randomly selected subset of the output layer’s activations are dropped, when training with
DropConnect we drop a randomly subsets of weights. With DropAll we can perform both methods
simultaneously. We show the validity of our proposals by improving the classification error on a
common image classification benchmark
Skin lesion classification from dermoscopic images using deep learning techniques
The recent emergence of deep learning methods for medical image analysis has enabled the development of intelligent medical imaging-based diagnosis systems that can assist the human expert in making better decisions about a patient’s health. In this paper we focus on the problem of skin lesion classification, particularly early melanoma detection, and present a deep-learning based approach to solve the problem of classifying a dermoscopic image containing a skin lesion as malignant or benign. The proposed solution is built around the VGGNet convolutional neural network architecture and uses the transfer learning paradigm. Experimental results are encouraging: on the ISIC Archive dataset, the proposed method achieves a sensitivity value of 78.66%, which is significantly higher than the current state of the art on that dataset.Postprint (author's final draft
Framework générique et unifié de social engineering
L’objectif de ce travail est de fournir un framework générique et unifié permettant de générer des rapports ou audits sur la santé sécuritaire IT des entreprises sous l’angle du social engineering, en pilotant ou automatisant des outils Open-Source phares du marché ou en développement in house. Afin de nous amener vers la réalisation de cet objectif, un état de l’art des frameworks de social engineering (SE), des formes de SE ainsi que des outils Open-Source permettant de réaliser le niveau de réponse de la cible visée face au social engineering est réalisé. À l’aide de matrices décisionnelles, nous comparons les outils cités dans l’état de l’art afin d’en retenir les plus adaptés à ce projet. Au travers de cette étude, nous choisissons également le langage de programmation de l’outil ainsi que le framework à utiliser
Digital analytics: an approach for data quality control
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceWith the emergence of the Digital Era, a new way of analyzing customers' behavior also emerged. It's not only about analyzing data from traditional data warehouses but also about measuring users' digital footprint on websites, mobile applications, and other digital data sources. Nowadays, companies collect data on their digital channels to improve website design and user experience, optimize e-commerce, track, and measure the success of actions and programs, identify problems, and improve the digital channels' performance. But the question that arises is how valid, accurate, and complete the data is. Do digital analysts understand each data point they have at their disposal? In this internship report will be given a detailed view of the critical points of digital analytics data quality, the adjacent problems and a solution will be presented to support and help the digital analysts overcome some of the challenges in this area
Analysis of sales representatives’ profile in DellEMC Rio de Janeiro through the challenger sale model
Sales panorama has been changing through the years and even more since the 2008 global crisis. Since then, companies started to demand more from the suppliers and their sales representatives; especially in more the complex sectors like Information Technologies (IT). Companies have been adapting their sales strategies to increase sales; however few have studied the sales representatives’ behavior with the client. Based on the Challenger Sale model this project aims to study the sales representatives’ profile in an IT market leader – DellEMC, Rio de Janeiro. The project was developed as a unique case study due to the leadership characteristics’ of DellEMC, A questionnaire was developed and administered to DellEMC’s sales department. According to the Challenger Sale model, DellEMC’s sales representatives appeared to have characteristics from all the three model dimensions – Teaching for differentiation; Tailoring for resonance and Taking Control of the sale. However it was also recognized that some factors like organizational culture or market characteristics have an impact on the sales representatives’ behavior. This project has no intension on generalization but to refine the Challenger Sale model theory and applicability to the specific case of DellEMC.O panorama de vendas tem vindo a alterar-se ao longo dos tempos, e mais ainda desde a crise de 2008. Com esta mudança, as empresas e organizações começaram a ser mais exigentes com os seus fornecedores, e por consequência com os seus representantes de vendas. Este facto verificou-se principalmente no sector dos serviços, nomeadamente nas indústrias fornecedoras de soluções mais complexas, como é o caso da indústria das Tecnologias de Informação. Deste modo, as empresas têm vindo a adaptar a sua estratégia de modo a serem mais competitivas comercialmente; contudo apenas algumas se focaram no comportamento dos vendedores. Este projecto foi desenvolvido como um caso de estudo único pelas caracterÃsticas de lÃder de mercado da DellEMC no Rio de Janeiro, e procura estudar o perfil dos seus vendedores sob o paradigma do modelo de Venda Desafiadora. Para este estudo foi realizado um questionário, para ser respondido pelos membros da equipa de vendas da DellEMC, que aparentemente provaram ter caracterÃsticas relacionadas com as três dimensões do modelo – Ensinar para a diferenciação; Personalizar para encontrar eco e Controlar a venda. Apesar da se verificar a presença destas caracterÃsticas, foram encontrados outros factores crÃticos no comportamento dos vendedores como a cultura organizacional, ou as caracterÃsticas do mercado. Este projecto não tem como objectivo a generalização dos seus resultados, mas sim o aprofundamento da modelo de Venda Desafiadora e a sua aplicabilidade no caso especÃfico da DellEMC
Substance misuse among physicians: a still neglected problem
OBJECTIVE: To evaluate the opinions and attitudes about substance use among clinical physicians. METHOD: A hundred physicians of clinical areas were selected in a public hospital of São Paulo. All of them were asked to answer a questionnaire with some questions about drug use. 83% completed the research protocol properly. RESULTS: 60.2% of the interviewed clinicians think that physicians are more likely to develop substance use disorders than general population. 67.5% of them stated they knew a colleague presenting a substance use disorder and in that in 41.0% of the cases the abused substance was a psychotropic available on the surgery facilities. However, 96.4% of the participants denied they could have a substance use problem, although 16.9% declared they had already used non prescribed psychotropics. Benzodiazepines were the most frequently used substances. In addition, 88.0% of them consider it was difficult to search for medical help. They added that a service exclusive for physicians would make this search easier. Nevertheless, 56.6% are not aware of the existence of such a service. CONCLUSION: Non-prescribed psychotropic use was high. However, most part of the clinicians does not consider this a problem. Most of the professionals do not know programs on substance use disorders specific for physicians, what would be a very positive initiative according to great part of them.OBJETIVO: Avaliar as impressões e as opiniões de médicos de áreas clÃnicas acerca do uso de drogas entre médicos e, mais especificamente, em ambiente cirúrgico. MÉTODOS: Foram sorteados 100 médicos não-residentes de áreas clÃnicas, selecionados ao acaso entre os profissionais com vÃnculo em um hospital público de São Paulo. Destes, 83 concluÃram o estudo, respondendo perguntas sobre o uso de drogas entre médicos. RESULTADOS: Declararam conhecer algum colega com problemas relacionados ao uso de substâncias 67,5% dos médicos. Esse Ãndice foi de 41,0% quando a pergunta era acerca de drogas disponÃveis em ambiente cirúrgico, visto que 68,6% julgam ser fácil o desvio de psicotrópicos desse local. Além disso, 60,2% acreditam que os médicos são mais suscetÃveis ao uso abusivo de psicotrópicos quando comparados à população geral. No entanto, 88,0% do total consideram difÃcil a procura por ajuda especializada. A porcentagem é de 56,6% dos que não conhecem serviço de atendimento direcionado exclusivamente para esses profissionais, algo que, na opinião de 83,1%, facilitaria a busca por tratamento. Dos participantes, 96,4% declararam não apresentar problemas relacionados ao uso de substâncias, ainda que 16,9% admita já ter feito uso de psicotrópicos sem prescrição. CONCLUSÃO: A freqüência de uso de psicotrópicos sem prescrição foi elevada. No entanto, parcela considerável não considera isso problema. A maioria dos profissionais não conhece serviços de atendimento especÃfico para médicos.Universidade Federal de São Paulo (UNIFESP) Departamento de Psiquiatria Programa de Orientação e Atendimento a DependentesUNIFESP, Depto. de Psiquiatria Programa de Orientação e Atendimento a DependentesSciEL
A time-dependent density functional theory scheme for efficient calculations of dynamic (hyper)polarizabilities
We present an efficient perturbative method to obtain both static and dynamic
polarizabilities and hyperpolarizabilities of complex electronic systems. This
approach is based on the solution of a frequency dependent Sternheimer
equation, within the formalism of time-dependent density functional theory, and
allows the calculation of the response both in resonance and out of resonance.
Furthermore, the excellent scaling with the number of atoms opens the way to
the investigation of response properties of very large molecular systems. To
demonstrate the capabilities of this method, we implemented it in a real-space
(basis-set free) code, and applied it to benchmark molecules, namely CO, H2O,
and paranitroaniline (PNA). Our results are in agreement with experimental and
previous theoretical studies, and fully validate our approach.Comment: 9 pages, 4 figure
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