A hybrid steepest descent method for constrained convex optimization

This paper describes a hybrid steepest descent method to decrease over time any given convex cost function while keeping the optimization variables in any given convex set. The method takes advantage of the properties of hybrid systems to avoid the computation of projections or of a dual optimum. The convergence to a global optimum is analyzed using Lyapunov stability arguments. A discretized implementation and simulation results are presented and analyzed. This method is of practical interest to integrate real-time convex optimization into embedded controllers thanks to its implementation as a dynamical system, its simplicity, and its low computation cost.     

Subpixel monitoring of the seasonal snow cover with MODIS at 250 m spatial resolution in the Southern Alps of New Zealand: Methodology and accuracy assessment

This study describes a comprehensive method to produce routinely regional maps of seasonal snow cover in the Southern Alps of New Zealand (upper Waitaki basin) on a subpixel basis, and with the MODerate Resolution Imaging Spectroradiometer (MODIS). The method uses an image fusion algorithm to produce snow maps at an improved 250 m spatial resolution in addition to the 500 m resolution snow maps. An iterative approach is used to correct imagery for both atmospheric and topographic effects using daily observations of atmospheric parameters. The computation of ground spectral reflectance enabled the use of image-independent end-members in a constrained linear unmixing technique to achieve a robust estimation of subpixel snow fractions. The accuracy of the snow maps and performance of the algorithm were assessed carefully using eight pairs of synchronic MODIS/ASTER images. ‘Pixel-based’ metrics showed that subpixel snow fractions were retrieved with a Mean Absolute Error of 6.8% at 250 m spatial resolution and 5.1% after aggregation at 500 m spatial resolution. In addition, a ‘feature-based’ metric showed that 90% of the snowlines were depicted generally within 300 m and 200 m of their correct position for the 500-m and 250-m spatial resolution snow maps, respectively. A dataset of 679 maps of subpixel snow fraction was produced for the period from February 2000 to May 2007. These repeated observations of the seasonal snow cover will benefit the ongoing effort to model snowmelt runoff in the region and to improve the estimation and management of water resources.     

Multi-level Motion Attention for Human Motion Prediction

International Journal of Computer Vision - Human motion prediction aims to forecast future human poses given a historical motion. Whether based on recurrent or feed-forward neural networks,...     

A multi-sensor approach for mapping plant-derived carbon storage in Amazonian podzols

The Rio Negro basin is characterized by the extensive occurrence of podzol-type soils that store large amounts of organic matter in depth, resulting in the storage of carbon able available to the atmosphere with climate change. The quantification of this carbon requires determination of podzol types and their spatial distribution. Remote-sensing techniques would be helpful in indirect spatializing and segmentation of soil groups in Amazonian podzols. Here we associated remote-sensing images (Shuttle Radar Topographic Mission (SRTM), Operational Land Imager sensor/Landsat 8, and Thermal Infrared Sensor/Landsat 8) and field sample data in order to achieve carbon stock mapping. We found that a multi-sensor approach was critical for a proper segmentation of vegetation groups and spatial distribution of areas with different hydrologic soil regimes.     

EGALITARIAN NEGOTIATIONS IN AGENT SOCIETIES

Achieving fairness among the members of a society is an important issue in many resource allocation problems. The increasing focus of the computer sciences community is motivated by a large panel of applications where other welfare notions do not suit. Centralized approaches are usually used, but they suffer from important drawbacks. Because relationships among society members are not considered, the provided resource allocation may not be achievable in practice. This study seeks to provide an evenly distributed approach based on a multiagent system, which overcomes the main drawbacks of centralized approaches. We provide an adaptive, anytime, and scalable algorithm to hold efficient egalitarian negotiations. Negotiation processes lead to socially efficient allocations as an emergent phenomenon. We also evaluate the “price of the social graph” toward the negotiation efficiency, and we provide the agent behavior to implement in order to achieve fair allocations.     

IODA: an interaction-oriented approach for multi-agent based simulations

Multi-Agent Systems (MAS) design methodologies and Integrated Development Environments exhibit many interesting properties that also support simulation design. Yet, in their current form, they are not appropriate enough to model Multi-Agent Based Simulations (MABS). Indeed, their design is focused on the functionalities to be achieved by the MAS and the allocation of these functionalities among software agents. In that context, the most important point of design is the organization of the agents and how they communicate with each other. On the opposite, MABS aim at studying emergent phenomena, the origin of which lies in the interactions between entities and their interaction with the environment. In that context, the interactions are not limited to exchanging messages but can also be fundamental physical interactions or any other actions involving simultaneously the environment and one or several agents. To deal with this issue, this paper presents the core notions of the Interaction-Oriented Design of Agent simulations (IODA) approach to simulation design. It includes a design methodology, a model, an architecture and also JEDI, a simple implementation of IODA concepts for reactive agents. First of all, our approach focuses on the design of an agent-independent specification of behaviors, called interactions. These interactions are not limited to the analysis phase of simulation: they are made concrete both in the model and at the implementation stage. In addition, no distinction is made between agents and objects: all entities of the simulation are agents. Owing to this principle, designing which interactions occur between agents, as well as how agents act, is achieved by means of an intuitive plug-and-play process, where interaction abilities are distributed among the agents. Besides, the guidelines provided by IODA are not limited to the specification of the model as they help the designer from the very beginning towards a concrete implementation of the simulation.     

High-grade efficiency III-nitrides semiconductor solar cell

Solar energy constitutes a widely available and further free energy. Several techniques have been used to permit a convenient exploitation of this clean energy, consisting in trying to extract the maximal amount of energy from simple devices. Therefore, these techniques suffer from reduced efficiency ratio, and they are neither well exploited nor developed.In this work, III-Nitrides semiconductors have been used instead of classical silicon. They possess the faculty to work in the maximum of the solar emission spectrum, hence offering a maximal efficiency, and also, due to their high energy gap, the surface reflection materialized by the reflectance is optimally reduced, always comparing with actual silicon-made devices.The computational methods used have shown that the theoretical efficiency obtained, in our paper, is near about 35%, depending greatly on the semiconductor purity.