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Laughter in stories of crime and tragedy : The importance of humor for marginalized populations

Humor is essential to social life, but it is often overlooked in the study of crime and other social problems. We introduce and make use of humor theory, emphasizing the theories of superiority and relief. Based on interviews with incarcerated men, we demonstrate how humor is used to criticize authorities, for self-aggrandizement, and to alleviate the pain of tragic experiences. Funny remarks and

Individualized Empirical Models of Carbohydrate and Insulin Effects on T1DM Blood Glucose Dynamics

ne of the main limiting factors in improving glucose control for T1DM subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing magnitude and duration of such effects would be useful not only for patients and physicians but also for the development of a controller targeting glycemia regulation. Therefore, in this paper we focus on estimating low-com

Model Checking a Self-Adaptive Camera Network with Physical Disturbances

The paper describes the design and verification of a self-adaptive system, composed of multiple smart cameras connected to a monitoring station, that determines the allocation of network bandwidth to the cameras. The design of such a system poses significant challenges, since multiple control strategies are active in the system simultaneously. In fact, the cameras adjust the quality of their strea

Continuous-Time Model Identification Using Non-Uniformly Sampled Data

This contribution reviews theory, algorithms, and validation results for system identification of continuous-time state-space models from finite input- output sequences. The algorithms developed are autoregressive methods, methods of subspace-based model identification and stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output mode

Control of Exhaust Recompression HCCI using Hybrid Model Predictive Control

Homogeneous Charge Compression Ignition (HCCI) holds promise for reduced emissions and increased efficiency compared to conventional internal combustion engines. As HCCI lacks direct actuation over the combustion phasing, much work has been devoted to designing controllers capable of set-point tracking and disturbance rejection. This paper presents results on model predictive control (MPC) of the

Direct Continuous Time System Identification of MISO Transfer Function Models applied to Type 1 Diabetes

This paper shows an application of continuous-time system identification methods to Type 1 diabetes. First, a general MISO transfer function structure with individual nominator and denominator polynomials for each input is assumed and a parameter estimation procedure via an iterative prediction error method presented. Then, the proposed identification method is evaluated on a simple simulation exa

Exploiting Task Redundancy in Industrial Manipulators during Drilling Operations

A drilling task requires a mechanism with five degrees of freedom, in order to achieve the correct position and orientation of the drilling tool. When performed with a standard 6-axes industrial robot, this task leaves an extra degree of freedom that can be exploited in order to achieve any additional criterion. Unfortunately, typical industrial robotic control architectures do not allow the user

Force Controlled Assembly of Emergency Stop Button

Modern industrial robots are fast and have very good repetitional accuracy, which have made them indispensable in many manufacturing applications. However, they are usually programmed to follow desired trajectories and only get feedback from position sensors. This works fine as long as the environment is very well structured, but does not give good robustness to objects not being positioned or gri

Continuous-Time Model Identification and State Estimation Using Non-Uniformly Sampled Data

This contribution reviews theory, algorithms, and validation results for system identification of continuous-time state-space models from finite input-output sequences. The algorithms developed are autoregressive methods, methods of subspace-based model identification and stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output model

Multi-step-ahead Multivariate Predictors: A Comparative Analysis

The focus of this article is to undertake a comparative analysis of multi-step-ahead linear multivariate predictors. The approach considered for the estimation will be based on geometrically reliable linear algebra tools, resorting to subspace identification methods. A crucial issue is quantification of both bias error and variance affecting the estimate of the prediction for increasing values of

Criteria for Global Stability of Coupled Systems with Application to Robust Output Feedback Design for Active Surge Control

The well-known and commonly accepted finite dimensional model qualitatively describing surge instabilities in centrifugal (and axial) compressors is considered. The problem of global output feedback stabilization for it is solved. The solution relies on two new criteria for global stability proposed for a class of nonlinear systems exploiting quadratic constraints for infinite sector nonlinearitie

Continuous-Time Model Identification and State Estimation Using Non-Uniformly Sampled Data

This paper presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite non-uniformly sampled input-output sequences. The algorithms developed are methods of model identification and stochastic realization adapted to the continuous-time model context using non-uniformly sampled input-output data. The resulting model can be decompose