271 research outputs found
A three critical points result in a bounded domain of a Banach space and applications
No full textUsing the bounded mountain pass lemma and the Ekeland variational principle we prove a bounded version of the Pucci-Serrin three critical points result in the intersection of a ball with a wedge in a Banach space. The localization constraints are overcome by boundary and invariance conditions. The result is applied to obtain multiple positive solutions for some semilinear problems
Weighted network analysis of high frequency cross-correlation measures
No full textIn this paper we implement a Fourier method to estimate high-frequency correlation matrices from small data sets. The Fourier estimates are shown to be considerably less noisy than the standard Pearson correlation measures and thus capable of detecting subtle changes in correlation matrices with just a month of data. The evolution of correlation at different time scales is analyzed from the full correlation matrix and its minimum spanning tree representation. The analysis is performed by implementing measures from the theory of random weighted networks. © 2007 The American Physical Society
A fixed point index approach to Krasnosel’skiĭ-Precup fixed point theorem in cones and applications
No full textWe present an alternative approach to the vector version of Krasnosel’skiĭ compression–expansion fixed point theorem due to Precup, which is based on the fixed point index. It allows us to obtain new general versions of this fixed point theorem and also multiplicity results. We emphasize that all of them are coexistence fixed point theorems for operator systems, that means that every component of the fixed points obtained is non-trivial. Finally, these coexistence fixed point theorems are applied to obtain results concerning the existence of positive solutions for systems of Hammerstein integral equations and radially symmetric solutions of (P1,P2) Laplacian systemsJorge Rodríguez–López was partially supported by Xunta de Galicia (Spain), project ED431C 2019/02 and AEI, Spain and FEDER , grant PID2020-113275GB-I00. The author thanks the referee for useful comments which led to the improvement of his paper and for the suggested additional referencesS
An H-infinity approach to optimal control of oxygen and carbon dioxide contents in blood
No full textScalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021)
No full textAbstractThe recent paper “Reward is Enough” by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all intelligence, both natural and artificial, and provides a suitable basis for the creation of artificial general intelligence. We contest the underlying assumption of Silver et al. that such reward can be scalar-valued. In this paper we explain why scalar rewards are insufficient to account for some aspects of both biological and computational intelligence, and argue in favour of explicitly multi-objective models of reward maximisation. Furthermore, we contend that even if scalar reward functions can trigger intelligent behaviour in specific cases, this type of reward is insufficient for the development of human-aligned artificial general intelligence due to unacceptable risks of unsafe or unethical behaviour
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021)
No full textAbstractThe recent paper “Reward is Enough” by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all intelligence, both natural and artificial, and provides a suitable basis for the creation of artificial general intelligence. We contest the underlying assumption of Silver et al. that such reward can be scalar-valued. In this paper we explain why scalar rewards are insufficient to account for some aspects of both biological and computational intelligence, and argue in favour of explicitly multi-objective models of reward maximisation. Furthermore, we contend that even if scalar reward functions can trigger intelligent behaviour in specific cases, this type of reward is insufficient for the development of human-aligned artificial general intelligence due to unacceptable risks of unsafe or unethical behaviour
A linear quadratic regulator for nonlinear SIRC epidemic model
No full textThe control of an epidemic disease consists in introducing the strategies able to reduce the number of infected subjects by means of medication/quarantine actions, and the number of the subjects that could catch the disease through an informative campaign and, when available, a vaccination strategy. Some diseases, like the influenza, do not guarantee immunity; therefore, the subjects could get ill again by different strain of the same viral subtype. The epidemic model adopted in this paper introduces the cross-immune individuals; it is known in literature as SIRC model, since the classes of susceptible (S), infected (I), removed (R) and cross-immune (C) subjects are considered. Its control is herein determined in the framework of the linear quadratic regulator, by applying to the original nonlinear model the optimal control found on the linearized system. The results appear satisfactory, and the drawback of using a control law based on the linear approximation of the system is compensated by the advantages arising from such a solution: no costate equations to be solved and a solution depending on the current state evolution which allows a feedback implementation
On the Role of Artificial Intelligence Methods in Modern Force-Controlled Manufacturing Robotic Tasks
No full textThis position paper explores the integration of Artificial Intelligence (AI) into force-controlled robotic tasks within the scope of advanced manufacturing, a cornerstone of Industry 4.0. AI’s role in enhancing robotic manipulators– key drivers in the Fourth Industrial Revolution– is rapidly leading to significant innovations in smart manufacturing. The objective of this article is to frame these innovations in practical force-controlled applications– e.g. deburring, polishing, and assembly tasks like peg-in-hole (PiH)– highlighting their ne cessity for maintaining high-quality production standards. By reporting on recent AI-based methodologies, this article contrasts them and identifies current challenges to be addressed in future research. The analysis concludes with a perspective on future research directions, emphasizing the need for common performance metrics to validate AI techniques, integration of various enhancements for performance optimization, and the importance of validating them in relevant scenarios. These future directions aim to provide consistency with already adopted approaches, so as to be compatible with manufacturing standards, increasing the relevance of AI-driven methods in both academic and industrial contexts
Virtuality, Innovation and R&D Activities
No full textInnovation plays a central role in economic development, at regional and national level. In the competitive environment companies are obliged to produce more rapidly, more effectively and more efficiently in new product development which is a result of research and development (R&D) activities. It is necessary for them to put together different capabilities and services with the goal, through cooperation between suppliers and customers, service providers and scientific institutions to achieve innovations of high quality. Depending on the type of industry, the type of business, the type of innovation and the strategic objectives that have been set, firms will regularly have to modify the way in which their R&D and innovation is organized. Nowadays shift from serial to simultaneous and parallel working in innovation has become more commonplace. Literature's have shown that collaboration is as a meta-capability for innovation. By a comprehensive reviewing of literature this article after define a virtual teams and its characteristics, addressing virtual environments innovation and the relationship to R&D activities. Finally conclude that innovation cannot be successful unless the knowledge and information in the R&D project are effectively captured, shared and internalized by the R&D project’s virtual team members.Innovation, Virtual teams, R&D
Applicability of Asymptotic Tracking in Case of Type 1 Diabetes
No full textThe alarming increasing tendency of diabetes population attracts technological interest too. From an engineering point of view, the treatment of diabetes mellitus can be represented by an outer control loop, to replace the partially or totally deficient blood glucose control system of the human body. To acquire this “artificial pancreas” a reliable glucose sensor and an insulin pump is needed as hardware, and a control algorithm to ensure the proper blood glucose regulation is needed as software. The latter is a key point of the diabetes “closing the loop” problem and its primary prerequisite is a valid model able to describe the blood glucose system. In the current chapter one of the most widely used and complex nonlinear model will be investigated with a dual purpose. Specific control aspects are discussed in the literature only on linearized versions; however, differential geometric approaches give more general formalization. As a result our first aim is to hide the nonlinearity of the physiological model by transforming the control input provided by a linear controller so that the response of the model would mimic the behavior of a linear system. Hence, the validity of linear controllers can be extended from the neighborhood of a working point to a larger subset of the state-space bounded by specific constraints. On the other hand, applicability of the nonlinear methodology is tested on a simple PID control based algorithm compared with LQG optimal method. Simulations are done under MATLAB on realistic input scenarios. Since the values of the state variables are needed Kalman filtering is used for state estimation
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