A Methodology for Modeling and Optimizing Social Systems

Abstract

A system methodology for modeling and optimizing social systems is presented. It allows constructing dynamical models formulated stochastically, i.e., their results are given by confidence intervals. The models provide optimal intervention ways to reach the stated objectives. Two optimization methods are used: (1) to test strategies and scenarios and (2) to optimize with a genetic algorithm. The application case presented is a small nonformal education Spanish business. First, the model is validated in the 2008–2012 period, and subsequently, the optimal way to obtain a maximum profit in the 2013–2025 period is obtained using the two methods.     

Price competition between a macrocell and a small-cell service provider with limited resources and optimal bandwidth user subscription: a game-theoretical model

The ever-increasing demand for higher data rates in wireless commutations provides a rationale for small cells deployment. While the physical and technological aspects of small-cell networks have been extensively studied in recent years, the economic analysis has received much less attention. We focus on the economic rationale for a small-cell service provider (SSP) operating a market where an incumbent macrocell service provider (MSP) exists, and competition develops. We analyze such scenario for the case of fixed users by means of Game Theory, specifically through a two-stage game: in the first stage each service provider posts its price according to a Stackelberg game where the MSP is the leader and the SSP is the follower; and, in the second stage, each user chooses both which provider to subscribe to and the optimal amount of bandwidth. A subgame perfect Nash equilibrium is used as a solution concept, and it is derived analytically. We show that the SSP has an incentive to operate in the market and its profit gets higher as SSP’s resources increase. Furthermore, users benefit from SSP’s operation, which may provide a rationale for a regulatory authority to grant the SSP access to the market, despite the fact that MSP’s profit is harmed. Finally, we identify two modes of operation of the system, which depend on the SSP coverage: one where SSP’s deployment is limited and the MSP strategy is not affected by SSP competition and takes only the users outside the SSP coverage; and another, where the SSP covers a large area and the MSP competes against the SSP taking a fraction of the users inside the small cells.     

An ecosystemic approach for assessing the urban water self-sufficiency potential: lessons from the Mediterranean

Frequent water stress episodes affecting urban hubs have caused a shift in urban water management towards integrated approaches and motivated a search for alternative water resources. Large-scale rainwater harvesting on the municipal scale can overcome the disadvantages of climate dependence and the volume restrictions associated with small-scale collection facilities. In this paper, two tools based on the urban metabolism concept are used to determine the water self-sufficiency potential of urban systems from urban runoff: a simple water self-sufficiency potential indicator and a socioeconomic water flow accounting scheme, which includes water losses. Both tools are applied to a densely populated coastal area that exemplifies urban centres in the Mediterranean. This approach is useful for regions with restricted data availability on water use and facilitates information dissemination to policy makers. The results indicate a significant water self-sufficiency potential for the area of study, even under projections of reduced precipitation in the area.     

Analysis of thermal infrared data from the Digital Airborne Imaging Spectrometer

Thermal infrared data of the Digital Airborne Imaging Spectrometer (DAIS), whose channels 74-79 are in the 8-13 w m waveband region, were analysed with the aim of recovering land surface temperature (LST). DAIS images were acquired over an experimental site where field and laboratory emissivity measurements were performed, and these were used to recover the LST from the six DAIS thermal channels. Atmospheric correction of DAIS data was calculated by means of a nearby radiosounding and a radiative transfer model. DAIS derived LSTs were compared with ground measurements of LST made coincidentally for a few test fields, the central DAIS channels yielding temperatures up to 10°C higher than ground measurements. A linear calibration was performed using in situ measurements of temperature and emissivity for two reference fields, and the large differences in temperature were then considerably reduced. Temperatures obtained from DAIS channel 79 agreed with the in situ measurements within - 2°C. This channel seemed the most reliable for deriving accurate LSTs in the dataset analysed here.     

Effective wavenumber for thermal infrared bands-application to Landsat-TM

In this paper we suggest that brightness temperature from the band radiance measured by a thermal sensor using Planck's law can be obtained along with effective parameters adequate for a given band, and a given temperature range. We propose an accurate algorithm to obtain these parameters (effective wavenumber or effective wavelength), which is based on Taylor's expansion of the exponential function that appears in Planck's equation. The dependence of the effective wavenumber on temperature has been investigated and the advantages of working with large temperature ranges have been analysed. We have compared the effective wavenumbers obtained with this algorithm to the parameters provided by NOAA/NESDIS and the maximum difference obtained has been 0.5 cm-1. The method has been applied to Landsat-Thematic Mapper band-6 and the results indicate that the error in temperature determination of the method is less than 0.01 K. A comparison with other published algorithms is also included.     

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. Although the optimum anticipation time depends on system parameters, we find that its value changes very little when the system parameters vary within a reasonable range. We also find that, in terms of system performance, deploying prediction is always advantageous when compared to a system without prediction, even when the system parameters are estimated with poor precision.     

Superconducting Vortex Lattice Configurations on Periodic Potentials: Simulation and Experiment

Nb films have been fabricated on top of array of Ni nanodots. The array of periodic pinning potentials modifies the vortex lattice for specific values of the external applied magnetic field. By means of an implemented code developed from scratch, computer simulations based only on the vortex?Cvortex and the vortex?Cnanodot interactions provide the total interaction between vortices and pinning sites as well as the position of the vortices in the array unit cell. This simulation approach could be performed on square, rectangular or triangular arrays of nanodefects of different size.