177,204 research outputs found
A hybrid model predictive control scheme for multi-agent containment and distributed sensing
No full textThis paper deals with distributed sensing over a field by means of a multi-agent control architecture. A leader/follower scheme is built up for exploring an environment by properly sensing areas of interest. By means of a control architecture based on decentralized Model Predictive Control (MPC), the leaders determine the regions to be sensed and the followers, which are only required to communicate with a subgroup of leaders, properly move in the space, constrained by the convex hull of their leaders, in order to perform the sensing task
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Contractive distributed MPC for consensus in networks of single and double integrators
No full textIn this paper we propose an application of distributed model predictive control techniques to the problem of driving a group of autonomous agents towards a consensus point, i.e. a negotiated position in their state space. Agents are assumed to be governed by discrete-time single- or double-integrator dynamics and the communication network can be directed and time-varying. Our control protocols are called contractive due to a specific constraint imposed on the agents' state path. Consensus is formally proven, also in presence of bounds on the norm of the inputs, by means of a geometrical analysis of the optimal paths
Combined computational study of mechanical behaviour and drug delivery from a porous, hydroxyapatite-based bone graft
No full textThis paper presents a numerical model of a porous, hydroxyapatite-based bone graft also suitable as a
drug delivery device. The graft was positioned in different
sites and with different porosities inside a human femur
model. The structural analyses were carried out to verify the
graft mechanical strength, using the Tsai–Wu criterion, and
the maximum porosity at which static failure does not occur.
A local stress shielding risk was also calculated as the ratio
between the bone stress in the intact condition and the stress
after implantation of the graft. Drug release kinetics was calculated by means of the finite element method. High porosity
grafts were found to fail in all implantation sites. Lower
porosity grafts showed to have adequate strength if implanted
in some positions, while provided insufficient resistance for
other implantation sites. Drug release kinetics was found to
be strongly dependent both on the porosity of the graft and
the bone density near the bone-graft interface
Model Predictive Control Schemes for Consensus in Multi-agent Systems with Integrator Dynamics and Time-varying Communication
No full textIn this paper we address the problem of driving a group of agents towards
a consensus point when agents have a discrete-time integrator dynamics and
the communication graph is time-varying. We propose two decentralized Model
Predictive Control (MPC) schemes that take into account constraints on the
agents’ inputs and show that they guarantee consensus under mild assumptions.
Since the global cost does not decrease monotonically, it cannot be used as
a Lyapunov function for proving convergence to consensus. Rather, our proofs
exploit geometric properties of the optimal path followed by individual agents
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Model Predictive Control Schemes for Consensus in Multi-Agent Systems with Single- and Double-Integrator Dynamics
No full textIn this paper we address the problem of driving a group of agents towards a consensus point when the agents have a discrete-time single- or double-integrator dynamics and the communication network is time-varying. We propose decentralized Model Predictive Control (MPC) schemes that take into account constraints on the agents' input and show that they guarantee consensus under mild assumptions. Since the global cost does not decrease monotonically, it cannot be used as a Lyapunov function for proving convergence to consensus. For this reason, our proofs exploit geometric properties of the optimal path followed by individual agents
A Model Predictive Control Scheme for Consensus in Multi-Agent Systems with Single-Integrator Dynamics and Input Constraints
No full textIn this paper we address the problem of driving
a group of agents towards a consensus point when agents have
a discrete-time single-integrator dynamics and the communication
graph is undirected and time-varying. We propose a
decentralized Model Predictive Control (MPC) scheme that
takes into account constraints on the agent inputs and show
that it guarantees consensus under mild assumptions. Since the
global cost does not decrease monotonically, it cannot be used as
a Lyapunov function for proving consensus. Rather, our proof
exploits geometric properties of the optimal path followed by
individual agents
Letter from R. R. Zellick, Assistant Trust Officer, Anglo California National Bank of San Francisco, to Joseph R. Goodman, October 2, 1942
No full textLetter from R. R. Zellick, Assistant Trust Officer at The Anglo California National Bank of San Francisco, to Joseph R. Goodman, regarding property owned by Dave Tatsuno. Zellick mentions a dispute between current tenants and Tatsuno, and that Tatsuno has asked Goodman to help locate trustworthy tenants.Personal correspondence, organizational records, government documents, publications, and other papers created or collected by Joseph R. Goodman documenting the forced removal and incarceration of Japanese Americans during World War II, as well as organized resistance to incarceration. Included in the collection are records of the Japanese Young Men's Christian Association and the Japanese American Citizens' League in San Francisco, including papers of the Japanese YMCA's executive secretary Lincoln Kanai; Sakai family papers; Goodman's correspondence to and from Japanese American incarcerees, organizations opposing forced removal and incarceration of Japanese Americans, the War Relocation Authority, and others; publications, photographs, and ephemera from the Topaz Relocation Center, where Goodman taught high school; War Relocation Authority records and publications; and newspaper clippings, pamphlets, and reports about forced removal and incarceration created by various government, religious, and civic organizations, in California and nationwide
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