In this paper we propose a decentralized nonlinear controller that has the ability to enhance the transient stability and achieve voltage regulation simultaneously for multimachine power systems. This paper extends th...
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Modern companies must be able to react in a timely way to changes in production and financial information since quick responses provide advantages against competition. As a matter of example, in automated trading syst...
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ISBN:
(纸本)9781467328432
Modern companies must be able to react in a timely way to changes in production and financial information since quick responses provide advantages against competition. As a matter of example, in automated trading systems a delay of 1 ms may be worth $1M. In addition, nowadays business decisions are made on the basis of increasing volumes of information, complicating the adoption of decisions on time. These requirements are common to those found in other real-time application domains. Consequently, adapting certain tools used in such domains may be a solution for business applications too. This paper draws several scenarios where middleware based solutions are justified, with particular insight on real-time behavior and control of QoS (Quality of Service) needs. More specifically, we provide certain guidelines to use OMG DDS (Data Distribution Service) as communications backbone in soft real-time business applications. DDS is a recent publish/subscribe middleware specification which provides mechanisms aimed at easing the creation of complex distributed applications such as those allowing the definition of content filters or tuning QoS parameters. Unfortunately, DDS is a complex technology so the programmers of business applications may benefit from certain guidelines that help them in the identification of the topics as well as the values for the QoS parameters provided by DDS.
We propose a distributed learning algorithm for fair scheduling in common-pool games. Common-pool games are strategic-form games where multiple agents compete over utilizing a limited common resource. A characteristic...
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Cognitive radio has emerged as a potential solution to the problem of spectrum scarcity. Cooperative spectrum sensing exploits the spatial diversity between cognitive radios for reliable detection of primary users'...
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This work presents the tools and procedure developed by the authors to create synchronous collaborative virtual and remote laboratories within a web course produced with a learning management system. Thanks to them, a...
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This work presents the tools and procedure developed by the authors to create synchronous collaborative virtual and remote laboratories within a web course produced with a learning management system. Thanks to them, an instructor can prepare virtual and/or remote laboratories and easily add them to its online web course, automatically obtaining collaborative features. Also, any member (either a student or a teacher), as long as s/he is enrolled in the course, can use the system to invite other enrolled users to a real-time collaborative experimental session with any of the laboratories that belong to that course. The extension tools presented in this work are based in two different free and open source software programs: Moodle as the learning management system that offers the web environment and Easy Java Simulations for creating the virtual and remote laboratories with collaborative support.
This paper emphasize the way in which the co-creation of value can profit from semantic-driven social software, taking into consideration the case of educational services delivered in the cloud. The solution is delive...
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This paper emphasize the way in which the co-creation of value can profit from semantic-driven social software, taking into consideration the case of educational services delivered in the cloud. The solution is delivered in the context of the POS-DRU Project no. 57748 “INSEED - Strategic Program Fostering Service Innovation Through Open, Continuous education” and it approaches conception and development of an open, collaborative, interactive environment to gather around universities, industry, governmental agencies and European institutions in order to foster service innovation by means of information / proves / technological transfer of the research results aiming to develop sustainable service systems solutions. In this respect, a specification proposal for a collaborative service process based on co-creation of value between educational service providers and consumers is presented. As a case study, a deployment proposal in the IBM Cloud environment for the INSEED project is depicted.
Given a linear system in a real or complex domain, linear regression aims to recover the model parameters from a set of observations. Recent studies in compressive sensing have successfully shown that under certain co...
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Given a linear system in a real or complex domain, linear regression aims to recover the model parameters from a set of observations. Recent studies in compressive sensing have successfully shown that under certain conditions, a linear program, namely, ℓ 1 -minimization, guarantees recovery of sparse parameter signals even when the system is underdetermined. In this paper, we consider a more challenging problem: when the phase of the output measurements from a linear system is omitted. Using a lifting technique, we show that even though the phase information is missing, the sparse signal can be recovered exactly by solving a semidefinite program when the sampling rate is sufficiently high. This is an interesting finding since the exact solutions to both sparse signal recovery and phase retrieval are combinatorial. The results extend the type of applications that compressive sensing can be applied to those where only output magnitudes can be observed. We demonstrate the accuracy of the algorithms through extensive simulation and a practical experiment.
Change detection has traditionally been seen as a centralized problem. Many change detection problems are however distributed in nature and the need for distributed change detection algorithms is therefore significant...
Change detection has traditionally been seen as a centralized problem. Many change detection problems are however distributed in nature and the need for distributed change detection algorithms is therefore significant. In this paper a distributed change detection algorithm is proposed. The change detection problem is first formulated as a convex optimization problem and then solved distributively with the alternating direction method of multipliers (ADMM). To further reduce the computational burden on each sensor, a homotopy solution is also derived. The proposed method have interesting connections with Lasso and compressed sensing and the theory developed for these methods are therefore directly applicable.
We present a novel identification framework that enables the use of first-order methods when estimating model parameters near a periodic orbit of a hybrid dynamical system. The proposed method reduces the space of ini...
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We present a novel identification framework that enables the use of first-order methods when estimating model parameters near a periodic orbit of a hybrid dynamical system. The proposed method reduces the space of initial conditions to a smooth manifold that contains the hybrid dynamics near the periodic orbit while maintaining the parametric dependence of the original hybrid model. First-order methods apply on this subsystem to minimize average prediction error, thus identifying parameters for the original hybrid system. We implement the technique and provide simulation results for a hybrid model relevant to terrestrial locomotion.
A method for detecting spikes and slow burst in photic evoked electroencephalogram (EEG) was proposed. The spikes were detected by combining methods of the morphological filter and the similarity coefficient in the ti...
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