Studying the interplay of party support and turnout [pre=print]

This chapter builds on earlier work (Franklin 2022) that explored the mechanism tying party choice at the individual level to election-level turnout rates. It employs CSES surveys from 28 countries over the course of 3 to 5 elections. It builds on past findings that used error correction models to confirm the role of negative feedback in maintaining equilibrium rates of party support; and elaborates on a parallel mechanism that helps to maintain an equilibrium level of turnout, through voter reactions to evolving levels of electoral competition. The chapter treats voter turnout, voterparty policy congruence, and party support as aspects of a single dynamic process at the party and birthyear-cohort levels, also helping to validate the dynamic account of turnout processes suggested in earlier work

Performance Evaluation of Hierarchical Simulation Systems

Simulation needs for design analysis, verification, and testing have become increasingly important as integrated circuit size and complexity have grown. One technique for dealing with this problem is to utilize hierarchical modeling and simulation methods. This paper presents an analysis of hierarchical simulation systems in terms of two performance measures; the number of statements required for describing a system, and the simulation system execution time associated with a given hierarchical system representation. A model of hierarchical simulation system performance is developed. The performance of the hierarchical simulator, lsim2, is examined through its use on the set of benchmark circuits and the results discussed in light of model predictions

The 2019 European Elections: Something old, something new, something borrowed, and something green

© 2020 Società Italiana di Scienza Politica. In the aftermath of a European Parliament (EP) election, there are normally two prominent aspects that receive attention by scholars and experts: the turnout rate and whether the Second Order Election (SOE) model proposed by Reif and Schmitt (1980) still applies. That model is based on the idea that, because EP elections do not themselves provide enough stimulus as to replace the concernsnormally present at national elections, the outcomes of EP elections in any participating country manifest themselves as a sort of distorted mirror of national (Parliamentary) elections in that country. The mirror is distorted because those national concerns are modified, not so much by the concerns arising from the European context in which EP elections are held as simply by the fact that EP elections are not national elections. In particular, at EP elections, national executive power is not at stake. The same party or parties will rule in each country after an EP election as ruled there before

One Dimensional Optimization on Multiprocessor Systems

This paper presents a straightforward approach to determining how best to utilize an MIMD multiprocessor in the solution of one dimensional optimization problems involving continuous unimodal functions and nongradient search techniques. A methodology is presented which allows one to consider a variety of speedup functions which may occur in parallel function and systems evaluation. It is shown how the best of two parallel optimization strategies can be determined for a given accuracy, number of processors and speedup function

Strategic Incentives, Issue Proximity and Party Support in Europe

The Issue Yield model predicts that parties will choose specific issues to emphasise, based on the joint assessment of electoral risks (how divisive is an issue within the party support base) and electoral opportunities (how widely supported is the same issue outside the party). According to this model, issues with high yield are those that combine a high affinity with the existing party base, together with a high potential to reach new voters. In previous work, the model showed a remarkable ability to explain aggregate issue importance as reported by party supporters, as well as issue emphasis in party manifestos. This paper tests the implications at the individual level by comparing a conventional model where issue salience is determined from manifesto data with a revised model where issue salience is determined by issue yield. The empirical findings show that issue yield is a more effective criterion than manifesto emphasis for identifying the issues most closely associated with party support in the minds of voters

Parallel Simulated Annealing

Since the paper by Kirkpatrick, Gelatt and Vecchi in 1983, the use of Simulated Annealing (SA) in solving combinatoric optimization problems has increased substantially. The SA algorithm has been applied to difficult problems in the difficult problems in the digital design automation such as cell placement and wire routing. While these studies have yielded good or near optimum solutions, they have required very long computer execution times (hours and days). These long times, coupled with the recent availability of the number of commercial parallel processors, has prompted the search for parallel implementations of the SA algorithm. The goal ahs been to obtain algorithmic speedup through the exploitation of parallelism. This paper presents a method for mapping the SA algorithm onto a dynamically structured tree of processors. Such a tree of processors can be mapped onto both shared memory and message based styles of parallel processors. The parallel SA (PSA) algorithm is discussed and its performance evaluated using simulation techniques. An important property of the PSA algorithm presented is that it maintains the same move decision sequence as the Serial SA (SSA) algorithm this avoiding problems associated with move conflicts, erroneous move acceptance/rejection decisions and oscillations which have been associated with other PSA algorithm proposals. The PSA algorithm presented fully preserves the convergence properties of the SSA algorithm with speedups varying roughly as log2N where N is the number of processors in the parallel processor

Estimating forest structure in a tropical forest using field measurements, a synthetic model and discrete return lidar data

Tropical forests are huge reservoirs of terrestrial carbon and are experiencing rapid degradation and deforestation. Understanding forest structure proves vital in accurately estimating both forest biomass and also the natural disturbances and remote sensing is an essential method for quantification of forest properties and structure in the tropics. Our objective is to examine canopy vegetation profiles formulated from discrete return LIght Detection And Ranging (lidar) data and examine their usefulness in estimating forest structural parameters measured during a field campaign. We developed a modeling procedure that utilized hypothetical stand characteristics to examine lidar profiles. In essence, this is a simple method to further enhance shape characteristics from the lidar profile. In this paper we report the results comparing field data collected at La Selva, Costa Rica (10° 26′ N, 83° 59′ W) and forest structure and parameters calculated from vegetation height profiles and forest structural modeling. We developed multiple regression models for each measured forest biometric property using forward stepwise variable selection that used Bayesian information criteria (BIC) as selection criteria. Among measures of forest structure, ranging from tree lateral density, diameter at breast height, and crown geometry, we found strong relationships with lidar canopy vegetation profile parameters. Metrics developed from lidar that were indicators of height of canopy were not significant in estimating plot biomass (p-value = 0.31, r2 = 0.17), but parameters from our synthetic forest model were found to be significant for estimating many of the forest structural properties, such as mean trunk diameter (p-value = 0.004, r2 = 0.51) and tree density (p-value = 0.002, r2 = 0.43). We were also able to develop a significant model relating lidar profiles to basal area (p-value = 0.003, r2 = 0.43). Use of the full lidar profile provided additional avenues for the prediction of field based forest measure parameters. Our synthetic canopy model provides a novel method for examining lidar metrics by developing a look-up table of profiles that determine profile shape, depth, and height. We suggest that the use of metrics indicating canopy height derived from lidar are limited in understanding biomass in a forest with little variation across the landscape and that there are many parameters that may be gleaned by lidar data that inform on forest biometric properties