Vendor Ranking, March 22, 2012

Vendor Ranking for letting reports from the Iowa Department of Transportation.

A probabilistic approach to niche-based community models for spatial forecasts of assemblage properties and their uncertainties

Aim Conservation strategies are in need of predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictions generally focus on deterministic processes and omit important stochastic processes and other unexplained variation in model outputs. Here we test a novel approach of community models that accounts for this variation and determine how well it reproduces observed properties of alpine butterfly communities. Location The western Swiss Alps. Methods We propose a new approach to process probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in the predictions of community properties. We test the utility of our novel approach against a traditional threshold-based approach. We used mountain butterfly communities spanning a large elevation gradient as a case study and evaluated the ability of our approach to model species richness and phylogenetic diversity of communities. Results S-SDMs reproduced the observed decrease in phylogenetic diversity and species richness with elevation, syndromes of environmental filtering. The prediction accuracy of community properties vary along environmental gradient: variability in predictions of species richness was higher at low elevation, while it was lower for phylogenetic diversity. Our approach allowed mapping the variability in species richness and phylogenetic diversity projections. Main conclusion Using our probabilistic approach to process species distribution models outputs to reconstruct communities furnishes an improved picture of the range of possible assemblage realisations under similar environmental conditions given stochastic processes and help inform manager of the uncertainty in the modelling results

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Ranking of HMA Moisture Sensitivity Tests in Iowa, RB00-012, 2012

Several agencies specify AASHTO T283 as the primary test for field acceptance of moisture susceptibility in hot mix asphalt. When used in this application, logistical difficulties challenge its practicality, while repeatability is routinely scrutinized by contractors. An alternative test is needed which can effectively demonstrate the ability to screen mixtures based on expected performance. The ideal replacement can be validated with field performance, is repeatable, and allows for prompt reporting of results. Dynamic modulus, flow number, AASHTO T283, Hamburg wheel tracking device (HWTD), and the moisture induced sensitivity test (MIST) were performed on plant produced surface mixes in Iowa. Follow-up distress surveys were used to rank the mixes by their performance. The rankings indicate both the quantity of swelling from MIST conditioning and submersed flow number matched the performance ranking of all but one mixture. Hamburg testing parameters also appear effective, namely the stripping inflection point and the ratio between stripping slope and the creep slope. Dynamic modulus testing was ineffective, followed by AASHTO T283 and ratios produced from flow number results of conditioned samples.

The Uncertain generalized probabilistic weighted average and its application in the theory of expertons

A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

mGPT: a probabilistic planner based on heuristic search

We describe the version of the GPT planner to be used in the planning competition. This version, called mGPT, solves mdps specified in the ppddllanguage by extracting and using different classes of lower bounds, along with various heuristic-search algorithms. The lower bounds are extracted from deterministic relaxations of the mdp where alternativeprobabilistic effects of an action are mapped into different, independent, deterministic actions. The heuristic-search algorithms, on the other hand, use these lower bounds for focusing the updates and delivering a consistent value function over all states reachable from the initial state with the greedy policy.

Graphical probabilistic analysis of the combination of items of evidence

Unlike the evaluation of single items of scientific evidence, the formal study and analysis of the jointevaluation of several distinct items of forensic evidence has to date received some punctual, ratherthan systematic, attention. Questions about the (i) relationships among a set of (usually unobservable)propositions and a set of (observable) items of scientific evidence, (ii) the joint probative valueof a collection of distinct items of evidence as well as (iii) the contribution of each individual itemwithin a given group of pieces of evidence still represent fundamental areas of research. To somedegree, this is remarkable since both, forensic science theory and practice, yet many daily inferencetasks, require the consideration of multiple items if not masses of evidence. A recurrent and particularcomplication that arises in such settings is that the application of probability theory, i.e. the referencemethod for reasoning under uncertainty, becomes increasingly demanding. The present paper takesthis as a starting point and discusses graphical probability models, i.e. Bayesian networks, as frameworkwithin which the joint evaluation of scientific evidence can be approached in some viable way.Based on a review of existing main contributions in this area, the article here aims at presentinginstances of real case studies from the author's institution in order to point out the usefulness andcapacities of Bayesian networks for the probabilistic assessment of the probative value of multipleand interrelated items of evidence. A main emphasis is placed on underlying general patterns of inference,their representation as well as their graphical probabilistic analysis. Attention is also drawnto inferential interactions, such as redundancy, synergy and directional change. These distinguish thejoint evaluation of evidence from assessments of isolated items of evidence. Together, these topicspresent aspects of interest to both, domain experts and recipients of expert information, because theyhave bearing on how multiple items of evidence are meaningfully and appropriately set into context.

Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks

Well developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in gunshot residue (GSR) particles, such analyses provide no information about a given particle's actual source. Possible origins for which scientists may need to account for are a primary exposure to the discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists in making the issue tractable within a probabilistic perspective. The proposed models focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment.

Senescence rates are determined by ranking on the fast-slow life-history continuum.

Comparative analyses of survival senescence by using life tables have identified generalizations including the observation that mammals senesce faster than similar-sized birds. These generalizations have been challenged because of limitations of life-table approaches and the growing appreciation that senescence is more than an increasing probability of death. Without using life tables, we examine senescence rates in annual individual fitness using 20 individual-based data sets of terrestrial vertebrates with contrasting life histories and body size. We find that senescence is widespread in the wild and equally likely to occur in survival and reproduction. Additionally, mammals senesce faster than birds because they have a faster life history for a given body size. By allowing us to disentangle the effects of two major fitness components our methods allow an assessment of the robustness of the prevalent life-table approach. Focusing on one aspect of life history - survival or recruitment - can provide reliable information on overall senescence.

Probabilistic algorithms for blind adaptive multiuser detection

In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

Ranking RegionalInnovation Policies: DEA-based Benchmarking in an European Setting

Seudullinen innovaatio on monimutkainen ilmiö, joka usein sijaitsee paikallisten toimijoiden keskinäisen vuorovaikutuksen kentässä. Täten sitä on perinteisesti pidetty vaikeasti mitattavana ilmiönä. Työssä sovellettiin Data Envelopment Analysis menetelmää, joka on osoittautunut aiemmin menestyksekkääksi tapauksissa, joissa mitattavien syötteiden ja tuotteiden väliset suhteet eivät ole olleet ilmeisiä. Työssä luotiin konseptuaalinen malli seudullisen innovaation syötteistä ja tuotteista, jonka perusteella valittiin 12 tilastollisen muuttujan mittaristo. Käyttäen Eurostat:ia datalähteenä, lähdedata kahdeksaan muuttujsta saatiin seudullisella tasolla, sekä mittaristoa täydennettiin yhdellä kansallisella muuttujalla. Arviointi suoritettiin lopulta 45 eurooppalaiselle seudulle. Tutkimuksen painopiste oli arvioida DEA-menetelmän soveltuvuutta innovaatio-järjestelmän mittaamiseen, sillä menetelmää ei ole aiemmin sovellettu vastaavassa tapauksessa. Ensimmäiset tulokset osoittivat ylipäätään liiallisen korkeita tehok-kuuslukuja. Korjaustoimenpiteitä erottelutarkkuuden parantamiseksi esiteltiin ja sovellettiin, jonka jälkeen saatiin realistisempia tuloksia ja ranking-lista arvioitavista seuduista. DEA-menetelmän todettiin olevan tehokas ja kiinnostava työkalu arviointikäytäntöjen ja innovaatiopolitiikan kehittämiseen, sikäli kun datan saatavuusongelmat saadaan ratkaistua sekä itse mallia tarkennettua.

Ranking-Dominance Relation for (Evolutionary) Multi-Objective Optimization

An alternative relation to Pareto-dominance relation is proposed. The new relation is based on ranking a set of solutions according to each separate objective and an aggregation function to calculate a scalar fitness value for each solution. The relation is called as ranking-dominance and it tries to tackle the curse of dimensionality commonly observedin evolutionary multi-objective optimization. Ranking-dominance can beused to sort a set of solutions even for a large number of objectives when Pareto-dominance relation cannot distinguish solutions from one another anymore. This permits search to advance even with a large number of objectives. It is also shown that ranking-dominance does not violate Pareto-dominance. Results indicate that selection based on ranking-dominance is able to advance search towards the Pareto-front in some cases, where selection based on Pareto-dominance stagnates. However, in some cases it is also possible that search does not proceed into direction of Pareto-front because the ranking-dominance relation permits deterioration of individual objectives. Results also show that when the number of objectives increases, selection based on just Pareto-dominance without diversity maintenance is able to advance search better than with diversity maintenance. Therefore, diversity maintenance is connive at the curse of dimensionality.

Ranking Regional Innovation Policies: DEA-based Benchmarking in an European Setting

Seudullinen innovaatio on monimutkainen ilmiö, joka usein sijaitsee paikallisten toimijoiden keskinäisen vuorovaikutuksen kentässä. Täten sitä on perinteisesti pidetty vaikeasti mitattavana ilmiönä. Työssä sovellettiin Data Envelopment Analysis menetelmää, joka on osoittautunut aiemmin menestyksekkääksi tapauksissa, joissa mitattavien syötteiden ja tuotteiden väliset suhteet eivät ole olleet ilmeisiä. Työssä luotiin konseptuaalinen malli seudullisen innovaation syötteistä ja tuotteista, jonka perusteella valittiin 12 tilastollisen muuttujan mittaristo. Käyttäen Eurostat:ia datalähteenä, lähdedata kahdeksaan muuttujsta saatiin seudullisella tasolla, sekä mittaristoa täydennettiin yhdellä kansallisella muuttujalla. Arviointi suoritettiin lopulta 45 eurooppalaiselle seudulle. Tutkimuksen painopiste oli arvioida DEA-menetelmän soveltuvuutta innovaatiojärjestelmän mittaamiseen, sillä menetelmää ei ole aiemmin sovellettu vastaavassa tapauksessa. Ensimmäiset tulokset osoittivat ylipäätään liiallisen korkeita tehokkuuslukuja. Korjaustoimenpiteitä erottelutarkkuuden parantamiseksi esiteltiin ja sovellettiin, jonka jälkeen saatiin realistisempia tuloksia ja ranking-lista arvioitavista seuduista. DEA-menetelmän todettiin olevan tehokas ja kiinnostava työkalu arviointikäytäntöjen ja innovaatiopolitiikan kehittämiseen, sikäli kun datan saatavuusongelmat saadaan ratkaistua sekä itse mallia tarkennettua.