Improving PPM with dynamic parameter updates

This article makes several improvements to the classic PPM algorithm, resulting in a new algorithm with superior compression effectiveness on human text. The key differences of our algorithm to classic PPM are that (A) rather than the original escape mechanism, we use a generalised blending method with explicit hyper-parameters that control the way symbol counts are combined to form predictions; (B) different hyper-parameters are used for classes of different contexts; and (C) these hyper-parameters are updated dynamically using gradient information. The resulting algorithm (PPM-DP) compresses human text better than all currently published variants of PPM, CTW, DMC, LZ, CSE and BWT, with runtime only slightly slower than classic PPM.This is the accepted manuscript. The final version is available at http://dx.doi.org/10.1109/DCC.2015.77

Optimization on fresh outdoor air ratio of air conditioning system with stratum ventilation for both targeted indoor air quality and maximal energy saving

Stratum ventilation can energy efficiently provide good inhaled indoor air quality with a proper operation (e.g., fresh outdoor air ratio). However, the non-uniform CO2 distribution in a stratum-ventilated room challenges the provision of targeted indoor air quality. This study proposes an optimization on the fresh outdoor air ratio of stratum ventilation for both the targeted indoor air quality and maximal energy saving. A model of CO2 concentration in the breathing zone is developed by coupling CO2 removal efficiency in the breathing zone and mass conservation laws. With the developed model, the ventilation parameters corresponding to different fresh outdoor air ratios are quantified to achieve the targeted indoor air quality (i.e., targeted CO2 concentration in the breathing zone). Using the fresh outdoor air ratios and corresponding ventilation parameters as inputs, energy performance evaluations of the air conditioning system are conducted by building energy simulations. The fresh outdoor air ratio with the minimal energy consumption is determined as the optimal one. Experiments show that the mean absolute error of the developed model of CO2 concentration in the breathing zone is 1.9%. The effectiveness of the proposed optimization is demonstrated using TRNSYS that the energy consumption of the air conditioning system with stratum ventilation is reduced by 6.4% while achieving the targeted indoor air quality. The proposed optimization is also promising for other ventilation modes for targeted indoor air quality and improved energy efficiency

Delta bloom filter compression using stochastic learning-based weak estimation

Substantial research has been done, and sill continues, for reducing the bandwidth requirement and for reliable access to the data, stored and transmitted, in a space efficient manner. Bloom filters and their variants have achieved wide spread acceptability in various fields due to their ability to satisfy these requirements. As this need has increased, especially, for the applications which require heavy use of the transmission bandwidth, distributed computing environment for the databases or the proxy servers, and even the applications which are sensitive to the access to the information with frequent modifications, this thesis proposes a solution in the form of compressed delta Bloom filter. This thesis proposes delta Bloom filter compression, using stochastic learning-based weak estimation and prediction with partial matching to achieve the goal of lossless compression with high compression gain for reducing the large data transferred frequently

Sustainable Cooperation in Global Climate Policy: Specific Formulas and Emission Targets to Build on Copenhagen and Cancun

We offer a framework to assign quantitative allocations of emissions of greenhouse gases (GHGs), across countries, one budget period at a time. Under the two-part plan: (i) China, India, and other developing countries accept targets at Business as Usual (BAU) in the coming budget period, the same period in which the US first agrees to cuts below BAU; and (ii) all countries are asked in the future to make further cuts in accordance with a common numerical formula to all. The formula is expressed as the sum of a Progressive Reductions Factor, a Latecomer Catch-up Factor, and a Gradual Equalization Factor. This paper builds on our previous work in many ways. First we update targets to reflect pledges made by governments after the Copenhagen Accord of December 2010 and confirmed at the Cancun meeting of December 2011. Second, the WITCH model, which we use to project economic and environmental effects of any given set of emission targets, has been refined and updated to reflect economic and technological developments. We include the possibility of emissions reduction from bio energy (BE), carbon capture and storage (CCS), and avoided deforestation and forest degradation (REDD+) which is an important component of pledges in several developing countries. Third, we use a Nash criterion for evaluating whether a country’s costs are too high to sustain cooperation.Cancun, Climate, Concentrations, Cooperation, Copenhagen, Costs, Developing Countries, Development, Emissions, Equity, Global Climate, Global Warming, Greenhouse Gas, Human Development, International, Kyoto, Sustainable, Treaty, United Nations, WITCH

IllinoisGRMHD: An Open-Source, User-Friendly GRMHD Code for Dynamical Spacetimes

In the extreme violence of merger and mass accretion, compact objects like black holes and neutron stars are thought to launch some of the most luminous outbursts of electromagnetic and gravitational wave energy in the Universe. Modeling these systems realistically is a central problem in theoretical astrophysics, but has proven extremely challenging, requiring the development of numerical relativity codes that solve Einstein's equations for the spacetime, coupled to the equations of general relativistic (ideal) magnetohydrodynamics (GRMHD) for the magnetized fluids. Over the past decade, the Illinois Numerical Relativity (ILNR) Group's dynamical spacetime GRMHD code has proven itself as a robust and reliable tool for theoretical modeling of such GRMHD phenomena. However, the code was written "by experts and for experts" of the code, with a steep learning curve that would severely hinder community adoption if it were open-sourced. Here we present IllinoisGRMHD, which is an open-source, highly-extensible rewrite of the original closed-source GRMHD code of the ILNR Group. Reducing the learning curve was the primary focus of this rewrite, with the goal of facilitating community involvement in the code's use and development, as well as the minimization of human effort in generating new science. IllinoisGRMHD also saves computer time, generating roundoff-precision identical output to the original code on adaptive-mesh grids, but nearly twice as fast at scales of hundreds to thousands of cores.Comment: 37 pages, 6 figures, single column. Matches published versio

Regional CO2 Inversion Through Ensemble-Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments

Atmospheric inversions provide estimates of carbon dioxide (CO2) fluxes between the surface and atmosphere based on atmospheric CO2 concentration observations. The number of CO2 observations is projected to increase severalfold in the next decades from expanding in situ networks and next-generation CO2-observing satellites, providing both an opportunity and a challenge for inversions. This study introduces the TRACE Regional Atmosphere-Carbon Ensemble (TRACE) system, which employ an ensemble-based simultaneous state and parameter estimation (ESSPE) approach to enable the assimilation of large volumes of observations for constraining CO2 flux parameters. TRACE uses an online full-physics mesoscale atmospheric model and assimilates observations serially in a coupled atmosphere-carbon ensemble Kalman filter. The data assimilation system was tested in a series of observing system simulation experiments using in situ observations for a regional domain over North America in summer. Under ideal conditions with known prior flux parameter error covariances, TRACE reduced the error in domain-integrated monthly CO2 fluxes by about 97% relative to the prior flux errors. In a more realistic scenario with unknown prior flux error statistics, the corresponding relative error reductions ranged from 80.6% to 88.5% depending on the specification of prior flux parameter error correlations. For regionally integrated fluxes on a spatial scale of 10(6) km(2), the sum of absolute errors was reduced by 34.5%-50.9% relative to the prior flux errors. Moreover, TRACE produced posterior uncertainty estimates that were consistent with the true errors. These initial experiments show that the ESSPE approach in TRACE provides a promising method for advancing CO2 inversion techniques

SIRU development. Volume 1: System development

A complete description of the development and initial evaluation of the Strapdown Inertial Reference Unit (SIRU) system is reported. System development documents the system mechanization with the analytic formulation for fault detection and isolation processing structure; the hardware redundancy design and the individual modularity features; the computational structure and facilities; and the initial subsystem evaluation results