We propose an independence criterion based on the eigen-spectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator (we term this a Hilbert-Schmidt Independence Criterion, or HSIC). This approach has several advantages, compared with previous kernel-based independence criteria. First, the empirical estimate is simpler than any other kernel dependence test, and requires no user-defined regularisation. Second, there is a clearly defined population quantity which the empirical estimate approaches in the large sample limit, with exponential convergence guaranteed between the two: this ensures that independence tests based on HSIC do not suffer from slow learning rates. Finally, we show in the context of independent component analysis (ICA) that the performance of HSIC is competitive with that of previously published kernel-based criteria, and of other recently published ICA methods.

Measuring statistical dependence with Hilbert-Schmidt norms

Presentacio sobre l'Oficina de Proteccio de Dades Personals de la UAB i la politica Open Science. Va formar part de la conferencia "Les politiques d'Open Data / Open Acces: Implicacions a la recerca" orientada a investigadors i gestors de projectes europeus que va tenir lloc el 20 de setembre de 2018 a la Universitat Autonoma de Barcelona

/pdf/general-data-protection-regulation-2z11cloyp7.pdf

General data protection regulation

Thank you very much for reading perturbation analysis of optimization problems. Maybe you have knowledge that, people have look hundreds times for their favorite books like this perturbation analysis of optimization problems, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they are facing with some malicious virus inside their computer. perturbation analysis of optimization problems is available in our book collection an online access to it is set as public so you can get it instantly. Our books collection saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the perturbation analysis of optimization problems is universally compatible with any devices to read.

Perturbation Analysis Of Optimization Problems

A surge of interest in explainable AI (XAI) has led to a vast collection of algorithmic work on the topic. While many recognize the necessity to incorporate explainability features in AI systems, how to address real-world user needs for understanding AI remains an open question. By interviewing 20 UX and design practitioners working on various AI products, we seek to identify gaps between the current XAI algorithmic work and practices to create explainable AI products. To do so, we develop an algorithm-informed XAI question bank in which user needs for explainability are represented as prototypical questions users might ask about the AI, and use it as a study probe. Our work contributes insights into the design space of XAI, informs efforts to support design practices in this space, and identifies opportunities for future XAI work. We also provide an extended XAI question bank and discuss how it can be used for creating user-centered XAI.

Questioning the AI: Informing Design Practices for Explainable AI User Experiences

Today, AI is being increasingly used to help human experts make decisions in high-stakes scenarios. In these scenarios, full automation is often undesirable, not only due to the significance of the outcome, but also because human experts can draw on their domain knowledge complementary to the model's to ensure task success. We refer to these scenarios as AI-assisted decision making, where the individual strengths of the human and the AI come together to optimize the joint decision outcome. A key to their success is to appropriately calibrate human trust in the AI on a case-by-case basis; knowing when to trust or distrust the AI allows the human expert to appropriately apply their knowledge, improving decision outcomes in cases where the model is likely to perform poorly. This research conducts a case study of AI-assisted decision making in which humans and AI have comparable performance alone, and explores whether features that reveal case-specific model information can calibrate trust and improve the joint performance of the human and AI. Specifically, we study the effect of showing confidence score and local explanation for a particular prediction. Through two human experiments, we show that confidence score can help calibrate people's trust in an AI model, but trust calibration alone is not sufficient to improve AI-assisted decision making, which may also depend on whether the human can bring in enough unique knowledge to complement the AI's errors. We also highlight the problems in using local explanation for AI-assisted decision making scenarios and invite the research community to explore new approaches to explainability for calibrating human trust in AI.

Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making

Actually, injuries are identified as persistent and serious problems in the sports activity Ankle sprains compose a significant part of these injuries and present high frequency, which increases the associated costs Among other issues, this condition is related to the common persistence of sequel and re-occurrences The disregard for its severity and a reduced follow-up of the treatment may be pointed as associated causes In this work, two Rugby athletes that were recovering from ankle sprains and receiving physiotherapeutic treatment were monitored Infrared thermography, a non-contact, non-invasive, non-ionizing, precise and fast medical imaging modality, has been used for analyzing the skin surface temperature distribution of the affected area The analysis of the collected thermograms has shown a positive evolution of treatment to the ankle sprain in both cases examined From the statistical analysis of the data, it was possible to differentiate the two cases presented, evidencing different recoveries In conclusion, by applying the developed and proposed methodology in these the two cases, it has been possible to confirm that infrared thermography may assume a relevant role in monitoring ankle sprains

/pdf/case-study-in-thermal-monitoring-of-physiotherapy-treatments-3mro5zuegt.pdf

Case Study in Thermal Monitoring of Physiotherapy Treatments to Ankle Sprains in Rugby Athletes

The extraction of morphometric features from images of biological structures is a crucial task for the study of several diseases. Particularly, concerning neuropathies, the state of the myelination process is vital for neuronal integrity and may be an indicator of the disease type and state. Few approaches exist to automatically analyse nerve morphometry and assist researchers in this time consuming task. The aim of this work is to develop an algorithm to detect axons and myelin contours in myelinated fibres of sciatic nerve images, thus allowing the automated assessment and quantification of myelination through the measurement of the g-ratio. The application of a directional gradient together with an active contour algorithm was able to effectively and accurately determine the degree of myelination in an imagiological dataset of sciatic nerves. It was obtained an average error of 1.80%, in comparison with the manual annotation performed by the specialist in all dataset.

Morphometric analysis of sciatic nerve images: A directional gradient approach

Bridges are the most vulnerable components in a road transport system. Thus, it is necessary that these structures are designed considering exceptional events. Among these events, earthquakes should not be ignored, since in the last decades representative seismic events, of magnitude greater than 5, happened in Brazil and were recorded by the Seismology Center of University of São Paulo (USP). Brazil has a specific standard for earthquake-resistant structures projects, but this excludes its use in special structures, such as bridges. In addition, many of these structures are not in ideal safety conditions, which makes them more vulnerable. This paper aims to assess the vulnerability of a typical bridge located in the Northeast of Brazil, since this region has one of the higher seismic risk in the country. The structural system presents a T-beam deck supported by non-integral “U” type abutments and by bents composed of two circular columns using elastomeric bearings. Numerical modeling is performed in OpenSees software and dynamic non-linear analyses are performed. Capacity models are obtained from Pushover analyses. Demand models are defined by incremental dynamic analyses using records collected from the Pacific Earthquake Engineering Research Center (PEER), which are compatible with target-spectrum for the city of Natal (RN). The vulnerability study is conducted through fragility curves, which provide the probability for different limit states of the structure. Finally, it is observed that the system fragility is conditioned by the elastomeric bearings that make the slide of the deck the most critical component, while columns do not suffer considerable damage with the increase in the intensity measure of seismic events

/pdf/estudo-de-fragilidade-de-uma-ponte-tipica-da-regiao-nordeste-204sgasmc7.pdf

Estudo de fragilidade de uma ponte típica da região nordeste do brasil. parte i: curvas de fragilidade.

This project deals with shaft finite element modeling using curved beam model. The objective is to evaluate the potential of replacing the current model of bowing, that neglects the inertia effects of the rotating shaft, for a more representative one, that includes such dynamic effects. The parameters used in the simulation will be the same as the built test bench, for comparison purposes. Depending on the results obtained in this project, the rotor-bearing model can be refined to achieve higher accuracy.

https://econtents.bc.unicamp.br/eventos/index.php/pibic/article/download/2374/2415

Eduardo M. Pereira

Papers

Case Study in Thermal Monitoring of Physiotherapy Treatments to Ankle Sprains in Rugby Athletes

Morphometric analysis of sciatic nerve images: A directional gradient approach

Estudo de fragilidade de uma ponte típica da região nordeste do brasil. parte i: curvas de fragilidade.

Modeling of shaft bow using finite element of curved beam