The paper introduces a novel method for controlling the shape of growth interfaces, such as the boundaries of dendritic crystals, described by a temperature-dependent geometrical evolution law, where the normal veloci...
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ISBN:
(纸本)9781479947287
The paper introduces a novel method for controlling the shape of growth interfaces, such as the boundaries of dendritic crystals, described by a temperature-dependent geometrical evolution law, where the normal velocity of the growing interface depends on both local curvature and temperature. Numerical simulations are provided to demonstrate the control approach.
In this issue of IEEE controlsystems Magazine, we speak with João Hespanha, who is a professor and chair of the department of electrical and Computer engineering and Director of the Center for control, Dynamical...
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Detection of melanoma in early stages is critical in terms of life expectancy of the patient and, also, in terms of treatment costs. In this context, we investigate the feasibility of implementing an algorithm that us...
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Detection of melanoma in early stages is critical in terms of life expectancy of the patient and, also, in terms of treatment costs. In this context, we investigate the feasibility of implementing an algorithm that uses nonstandardized color images of skin lesions for risk assessment. In this paper we present a methodology for real-time acquisition of quality verified images using smartphones. We also test a series of shape and texture parameters to determine their relevance in the context of providing an accurate risk profile for an analyzed lesion. Our conclusion is that risk assessment with high accuracy is possible even when using nonstandardized color images taken with a mobile device (smartphone) camera.
Peer review (e.g., review of research papers) is essential for the success of the scientific community. In peer review, the reviewers voluntarily exert costly effort in reviewing papers. Hence, it is important to desi...
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ISBN:
(纸本)9781479980109
Peer review (e.g., review of research papers) is essential for the success of the scientific community. In peer review, the reviewers voluntarily exert costly effort in reviewing papers. Hence, it is important to design mechanisms to elicit high effort from reviewers. Exploiting the fact that the researchers interact with each other repeatedly (e.g., by submitting and reviewing papers over years), we propose a rating and matching mechanism to elicit high effort from reviewers. Our proposed mechanism overcomes two major difficulties, namely adverse selection (i.e., the unidentifiable quality of heterogeneous reviewers) and moral hazard (i.e., the unobservable effort levels from reviewers). Specifically, our proposed mechanism assigns and updates ratings for the researchers, and matches researchers' papers to reviewers with similar ratings. In this way, the mechanism identifies different types of reviewers by their ratings, and incentivizes different reviewers to exert high effort. Focusing on the matching rule, we first provide design guidelines for a general matching rule that leads the system to an equilibrium, where the reviewers' types are identified and their high efforts are elicited. Then we study in detail a baseline matching rule that assigns each researcher's paper to one of the two reviewers with the closest ratings, provide guidelines of how to choose the initial ratings, and analyze equilibrium review quality and equilibrium ratings. Finally, we extend the baseline matching rule to two classes. The first extension provides extra reward and/or punishment by adjusting the probabilities of matching each researcher's paper to its neighbors. The second extension provides extra reward and/or punishment by allowing to match each researcher's paper to reviewers other than its neighbors. We prove that it is beneficial (in the sense that the optimal equilibrium review quality is higher) to reward reviewers in the first extension, and to punish reviewers in the sec
In this paper, we present a distributed estimation setup where local agents estimate their states from relative measurements received from their neighbours. In the case of heterogeneous multi-agent systems, where only...
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Robotic swarms have a great potential to solve in a simple way, without the need for a central controller, a wide range of difficult real-world problems, such as transportation, search and rescue missions etc. While t...
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Robotic swarms have a great potential to solve in a simple way, without the need for a central controller, a wide range of difficult real-world problems, such as transportation, search and rescue missions etc. While there are important results in what regards the emergence of complex behaviors from very simple interacting robots, the security of robotic swarms remains a problem which did not get the proper consideration. With the overall goal of enabling the full distributed security of a robotic swarm, the contributions of this paper are threefold. First, a bioinspired framework based on membrane computing (P colonies) is proposed for approaching this issue. Secondly, the functionalities of a P colonies simulator are presented and finally, the notion of P swarm is introduced as a relevant new formal model of safe interactions between robots in a swarm.
Robotic systems have changed and evolved dramatically over the last decades. However, old and modern robots continue to co-exist in research laboratories worldwide. Outdated robots lack sufficient computing power, and...
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Robotic systems have changed and evolved dramatically over the last decades. However, old and modern robots continue to co-exist in research laboratories worldwide. Outdated robots lack sufficient computing power, and need an improvement of their hardware and software capabilities. How to achieve that with minimal costs is a matter of concern of robotics researchers and practitioners. The main contribution of this paper is that it presents a concept solution and the first practical results for developing a SLAM (simultaneous localization and mapping) capable heterogeneous multi-robot system by using existing robots from multiple generations, adding new hardware such as a Kinect sensor and using open-source software.
Functional electrical stimulation (FES) based cycling exercise for paraplegics, with the aid of a flywheel and electrical clutch mechanism, is introduced. Fuzzy logic controllers are used to control the stimulation in...
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Functional electrical stimulation (FES) based cycling exercise for paraplegics, with the aid of a flywheel and electrical clutch mechanism, is introduced. Fuzzy logic controllers are used to control the stimulation intensity on the quadriceps muscle of both legs. The control of the flywheel assist mechanism is achieved using two different fuzzy logic based approaches. The first approach depends on the knee angular velocity of both legs of the trainee while the second approach uses the bicycle's crank cadence, with the angular velocity of the flywheel, to decide on the engagement/disengagement of the flywheel with the crank. A comparative assessment of the two approaches is carried out and the results are discussed. Results show that the second approach is promoting smoother and longer FES cycling exercise due to reduced stimulation intensity on the muscle, however, it requires a sensitive electrical clutch.
In this paper we analyze the computational complexity of a linear model predictive control (MPC) scheme for embedded systems based on the dual gradient algorithm. We recast our MPC problem as a linearly constrained co...
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In this paper we analyze the computational complexity of a linear model predictive control (MPC) scheme for embedded systems based on the dual gradient algorithm. We recast our MPC problem as a linearly constrained convex problem. When it is difficult to project on the primal feasible set described by linear constraints, we use the Lagrangian relaxation to handle the complicated constraints and then we apply the dual gradient algorithm for solving the corresponding dual. We give a full convergence rate analysis for dual gradient algorithm: we provide sublinear or linear estimates on the primal suboptimality and feasibility violation of the generated approximate primal solutions. Our analysis relies on the Lipschitz property of the dual function or an error bound property. Furthermore, the iteration complexity analysis is based on an approximate primal solution given by the last primal iterate sequence. We also discuss implementation aspects of the proposed algorithm on constrained linear MPC for embedded systems.
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