Bernstein-type operators which preserve polynomials

In this paper we present the sequence of linear Bernstein-type operators defined for f∈C[0,1] by B_n(f°τ⁻¹)°τ, B_n being the classical Bernstein operators and τ being any function that is continuously differentiable ∞ times on [0,1], such that τ(0)=0, τ(1)=1 and τ^′(x)>0 for x∈[0,1]. We investigate its shape preserving and convergence properties, as well as its asymptotic behavior and saturation. Moreover, these operators and others of King type are compared with each other and with B_n. We present as an interesting byproduct sequences of positive linear operators of polynomial type with nice geometric shape preserving properties, which converge to the identity, which in a certain sense improve B_n in approximating a number of increasing functions, and which, apart from the constant functions, fix suitable polynomials of a prescribed degree. The notion of convexity with respect to τ plays an important role.     

Autonomous motion planning of a hand-arm robotic system based on captured human-like hand postures

The paper deals with the problem of motion planning of anthropomorphic mechanical hands avoiding collisions and trying to mimic real human hand postures. The approach uses the concept of “principal motion directions” to reduce the dimension of the search space in order to obtain results with a compromise between motion optimality and planning complexity (time). Basically, the work includes the following phases: capturing the human hand workspace using a sensorized glove and mapping it to the mechanical hand workspace, reducing the space dimension by looking for the most relevant principal motion directions, and planning the hand movements using a probabilistic roadmap planner. The approach has been implemented for a four finger anthropomorphic mechanical hand (17 joints with 13 independent degrees of freedom) assembled on an industrial robot (6 independent degrees of freedom), and experimental examples are included to illustrate its validity.     

Non-invasive organization variation assessment in the onset and termination of paroxysmal atrial fibrillation

Atrial Fibrillation (AF) is the most common supraventricular tachyarrhythmia. Recently, it has been suggested that AF is partially organized on its onset and termination, thus being more suitable for antiarrhythmia and to avoid unnecessary therapy. Although several invasive and non-invasive AF organization estimators have been proposed, the organization time course in the first and last minutes of AF has not been quantified yet. The aim of this work is to study non-invasively the organization variation within the first and last minutes of paroxysmal AF. The organization was evaluated making use of sample entropy, which can robustly estimate electrical atrial activity organization from surface ECG recordings. This work proves an organization decrease in the first minutes of AF onset and an increase within the last minute before spontaneous AF termination. These results are in agreement with the conclusions reported by other authors who made use of invasive recordings.     

Design of interval observers for uncertain dynamical systems

Interval state observers provide an estimate on the set of admissible values of the state vector at each instant of time. Ideally, the size of the evaluated set is proportional to the model uncertainty, thus interval observers generate the state estimates with estimation error bounds, similarly to Kalman filters, but in the deterministic framework. Main tools and techniques for design of interval observers are reviewed in this tutorial for continuous-time, discrete-time and time-delayed systems.     

A note on interval observer design for unknown input estimation

This paper addresses the problem of interval observer design for unknown input estimation in linear time-invariant systems. Although the problem of unknown input estimation has been widely studied in the literature, the design of joint state and unknown input observers has not been considered within a set-membership context. While conventional interval observers could be used to propagate with some additional conservatism, unknown inputs by considering them as disturbances, the proposed approach allows their estimation. Under the assumption that the measurement noise and the disturbances are bounded, lower and upper bounds for the unmeasured state and unknown inputs are computed. Numerical simulations are presented to show the efficiency of the proposed approach.     

A neuro-genetic-simulated annealing approach to the inverse kinematics solution of robots: a simulation based study

In this study, a hybrid intelligent solution system including neural networks, genetic algorithms and simulated annealing has been proposed for the inverse kinematics solution of robotic manipulators. The main purpose of the proposed system is to decrease the end effector error of a neural network based inverse kinematics solution. In the designed hybrid intelligent system, simulated annealing algorithm has been used as a genetic operator to decrease the process time of the genetic algorithm to find the optimum solution. Obtained best solution from the neural network has been included in the initial solution of genetic algorithm with randomly produced solutions. The end effector error has been reduced micrometer levels after the implementation of the hybrid intelligent solution system.     

Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules

This paper presents a proposal for the extraction of association rules called G3PARM (Grammar-Guided Genetic Programming for Association Rule Mining) that makes the knowledge extracted more expressive and flexible. This algorithm allows a context-free grammar to be adapted and applied to each specific problem or domain and eliminates the problems raised by discretization. This proposal keeps the best individuals (those that exceed a certain threshold of support and confidence) obtained with the passing of generations in an auxiliary population of fixed size n. G3PARM obtains solutions within specified time limits and does not require the large amounts of memory that the exhaustive search algorithms in the field of association rules do. Our approach is compared to exhaustive search (Apriori and FP-Growth) and genetic (QuantMiner and ARMGA) algorithms for mining association rules and performs an analysis of the mined rules. Finally, a series of experiments serve to contrast the scalability of our algorithm. The proposal obtains a small set of rules with high support and confidence, over 90 and 99% respectively. Moreover, the resulting set of rules closely satisfies all the dataset instances. These results illustrate that our proposal is highly promising for the discovery of association rules in different types of datasets.     

Environmental Fatigue and Static Behavior of RC Beams Strengthened with Carbon-Fiber-Reinforced Polymer

Many countries around the world have tremendous needs to repair and strengthen their transportation infrastructure. Almost everywhere, traffic loads have reached levels largely exceeding design expectations. Northern countries also experience severe winter conditions that are combined with an extensive use of deicing salts and accelerate structural deterioration. In Canada, the extent of deterioration has prompted many authorities, including the federal and provincial governments, to investigate the potential use of fiber-reinforced polymer products to extend the life of their existing structures. However, it is widely recognized that the large-scale implementation of these products is often impaired by the lack of data on their durability. This paper presents an experimental project undertaken in order to assess the durability of reinforced concrete beams externally strengthened with two types of carbon-fiber-reinforced polymer (CFRP). The beams were first exposed to either wet-dry cycles or continuous immersion in water and then were loaded in fatigue. Finally, they were tested quasi-statically under four-point bending up to failure. The test results presented here provide some insights on the potential long-term performance of CFRP-strengthened beams exposed to severe environmental conditions.     

Characterisation of chickpea flour‐based gluten‐free batters and muffins with added biopolymers: rheological,physical and sensory properties

Chickpea flour (CF)‐based muffin formulations were made with CF alone and with added biopolymers [whey protein (WP), xanthan gum (XG) and inulin (INL)] to evaluate their suitability to be a wheat flour (WF) substitute in muffins. Structural characteristics of the batters and muffins were studied by means of rheometry, microscopy, physicochemical properties, and texture and sensory analysis. Partial replacement of CF with XG, alone (at 0.5 and 1%) or blended with either WP or INL, significantly increased the batter viscoelasticity as denser matrices developed; moreover, the muffins with XG added at 1% had similar hardness to wheat gluten muffins. The replacement of WF decreased the springiness, cohesiveness, chewiness, resilience and specific volume of the muffin. However, baked muffins with added XG also showed higher sensory sponginess and moisture associated with numerous air bubbles in the batter and were perceived to be easier to swallow and to have better general appearance.