Temporal-envelope constancy of speech in rooms and the perceptual weighting of frequency bands

Three experiments measured constancy in speech perception, using natural-speech messages or noise-band vocoder versions of them. The eight vocoder-bands had equally log-spaced center-frequencies and the shapes of corresponding “auditory” filters. Consequently, the bands had the temporal envelopes that arise in these auditory filters when the speech is played. The “sir” or “stir” test-words were distinguished by degrees of amplitude modulation, and played in the context; “next you’ll get _ to click on.” Listeners identified test-words appropriately, even in the vocoder conditions where the speech had a “noise-like” quality. Constancy was assessed by comparing the identification of test-words with low or high levels of room reflections across conditions where the context had either a low or a high level of reflections. Constancy was obtained with both the natural and the vocoded speech, indicating that the effect arises through temporal-envelope processing. Two further experiments assessed perceptual weighting of the different bands, both in the test word and in the context. The resulting weighting functions both increase monotonically with frequency, following the spectral characteristics of the test-word’s [s]. It is suggested that these two weighting functions are similar because they both come about through the perceptual grouping of the test-word’s bands.

Stated attribute non-attendance in successive choice experiments

Attribute non-attendance in choice experiments affects WTP estimates and therefore the validity of the method. A recent strand of literature uses attenuated estimates of marginal utilities of ignored attributes. Following this approach, we propose a generalisation of the mixed logit model whereby the distribution of marginal utility coefficients of a stated non-attender has a potentially lower mean and lower variance than those of a stated attender. Model comparison shows that our shrinkage approach fits the data better and produces more reliable WTP estimates. We further find that while reliability of stated attribute non-attendance increases in successive choice experiments, it does not increase when respondents report having ignored the same attribute twice.

Simple uncertainty frameworks for selecting weighting schemes and interpreting multimodel ensemble climate change experiments

Future climate change projections are often derived from ensembles of simulations from multiple global circulation models using heuristic weighting schemes. This study provides a more rigorous justification for this by introducing a nested family of three simple analysis of variance frameworks. Statistical frameworks are essential in order to quantify the uncertainty associated with the estimate of the mean climate change response. The most general framework yields the “one model, one vote” weighting scheme often used in climate projection. However, a simpler additive framework is found to be preferable when the climate change response is not strongly model dependent. In such situations, the weighted multimodel mean may be interpreted as an estimate of the actual climate response, even in the presence of shared model biases. Statistical significance tests are derived to choose the most appropriate framework for specific multimodel ensemble data. The framework assumptions are explicit and can be checked using simple tests and graphical techniques. The frameworks can be used to test for evidence of nonzero climate response and to construct confidence intervals for the size of the response. The methodology is illustrated by application to North Atlantic storm track data from the Coupled Model Intercomparison Project phase 5 (CMIP5) multimodel ensemble. Despite large variations in the historical storm tracks, the cyclone frequency climate change response is not found to be model dependent over most of the region. This gives high confidence in the response estimates. Statistically significant decreases in cyclone frequency are found on the flanks of the North Atlantic storm track and in the Mediterranean basin.

Visual attention and attribute attendance in multi-attribute choice experiments

Decision strategies in multi-attribute Choice Experiments are investigated using eye-tracking. The visual attention towards, and attendance of, attributes is examined. Stated attendance is found to diverge substantively from visual attendance of attributes. However, stated and visual attendance are shown to be informative, non-overlapping sources of information about respondent utility functions when incorporated into model estimation. Eye-tracking also reveals systematic nonattendance of attributes only by a minority of respondents. Most respondents visually attend most attributes most of the time. We find no compelling evidence that the level of attention is related to respondent certainty, or that higher or lower value attributes receive more or less attention

Using attribute importance rankings within discrete choice experiments: an application to valuing bread attributes

We present a new Bayesian econometric specification for a hypothetical Discrete Choice Experiment (DCE) incorporating respondent ranking information about attribute importance. Our results indicate that a DCE debriefing question that asks respondents to rank the importance of attributes helps to explain the resulting choices. We also examine how mode of survey delivery (online and mail) impacts model performance, finding that results are not substantively a§ected by the mode of survey delivery. We conclude that the ranking data is a complementary source of information about respondent utility functions within hypothetical DCEs

Finite sample weighting of recursive forecast errors

This paper proposes and tests a new framework for weighting recursive out-of-sample prediction errors according to their corresponding levels of in-sample estimation uncertainty. In essence, we show how to use the maximum possible amount of information from the sample in the evaluation of the prediction accuracy, by commencing the forecasts at the earliest opportunity and weighting the prediction errors. Via a Monte Carlo study, we demonstrate that the proposed framework selects the correct model from a set of candidate models considerably more often than the existing standard approach when only a small sample is available. We also show that the proposed weighting approaches result in tests of equal predictive accuracy that have much better sizes than the standard approach. An application to an exchange rate dataset highlights relevant differences in the results of tests of predictive accuracy based on the standard approach versus the framework proposed in this paper.

Multi-attribute collaborative filtering recommendation based on improved group decision-making

Currently researchers in the field of personalized recommendations bear little consideration on users' interest differences in resource attributes although resource attribute is usually one of the most important factors in determining user preferences. To solve this problem, the paper builds an evaluation model of user interest based on resource multi-attributes, proposes a modified Pearson-Compatibility multi-attribute group decision-making algorithm, and introduces an algorithm to solve the recommendation problem of k-neighbor similar users. Considering the characteristics of collaborative filtering recommendation, the paper addresses the issues on the preference differences of similar users, incomplete values, and advanced converge of the algorithm. Thus the paper realizes multi-attribute collaborative filtering. Finally, the effectiveness of the algorithm is proved by an experiment of collaborative recommendation among multi-users based on virtual environment. The experimental results show that the algorithm has a high accuracy on predicting target users' attribute preferences and has a strong anti-interference ability on deviation and incomplete values.

Modeling bidding competitiveness and position performance in multi-attribute construction auctions

Currently, multi-attribute auctions are becoming widespread awarding mechanisms for contracts in construction, and in these auctions, criteria other than price are taken into account for ranking bidder proposals. Therefore, being the lowest-price bidder is no longer a guarantee of being awarded, thus increasing the importance of measuring any bidder’s performance when not only the first position (lowest price) matters. Modeling position performance allows a tender manager to calculate the probability curves related to the more likely positions to be occupied by any bidder who enters a competitive auction irrespective of the actual number of future participating bidders. This paper details a practical methodology based on simple statistical calculations for modeling the performance of a single bidder or a group of bidders, constituting a useful resource for analyzing one’s own success while benchmarking potential bidding competitors.

Scoring rules and competitive behavior in best value construction auctions

This paper examines the extent to which engineers can influence the competitive behavior of bidders in Best Value or multi-attribute construction auctions, where both the (dollar) bid and technical non-price criteria are scored according to a scoring rule. From a sample of Spanish construction auctions with a variety of bid scoring rules, it is found that bidders are influenced by the auction rules in significant and predictable ways. The bid score weighting, bid scoring formula and abnormally low bid criterion are variables likely to influence the competitiveness of bidders in terms of both their aggressive/conservative bidding and concentration/dispersion of bids. Revealing the influence of the bid scoring rules and their magnitude on bidders’ competitive behavior opens the door for the engineer to condition bidder competitive behavior in such a way as to provide the balance needed to achieve the owner’s desired strategic outcomes.

Joint use of attribute importance rankings and non-attendance data in choice experiments

The joint and alternative uses of attribute non-attendance and importance ranking data within discrete choice experiments are investigated using data from Lebanon examining consumers’ preferences for safety certification in food. We find that both types of information; attribute non-attendance and importance rankings, improve estimates of respondent utility. We introduce a method of integrating both types of information simultaneously and find that this outperforms models where either importance ranking or non-attendance data are used alone. As in previous studies, stated non-attendance of attributes was not found to be consistent with respondents having zero marginal utility for those attributes

Dynamics of inter-modality re-weighting during human postural control

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Assessment of luteal function in goats by ultrasonographic image attribute analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mapeamento do relevo do embasamento de bacias sedimentares através da inversão gravimétrica vinculada

Apresentamos três novos métodos estáveis de inversão gravimétrica para estimar o relevo de uma interface arbitrária separando dois meios. Para a garantia da estabilidade da solução, introduzimos informações a priori sobre a interface a ser mapeada, através da minimização de um (ou mais) funcional estabilizante. Portanto, estes três métodos se diferenciam pelos tipos de informação físico-geológica incorporados. No primeiro método, denominado suavidade global, as profundidades da interface são estimadas em pontos discretos, presumindo-se o conhecimento a priori sobre o contraste de densidade entre os meios. Para a estabilização do problema inverso introduzimos dois vínculos: (a) proximidade entre as profundidades estimadas e verdadeiras da interface em alguns pontos fornecidas por furos de sondagem; e (b) proximidade entre as profundidades estimadas em pontos adjacentes. A combinação destes dois vínculos impõe uma suavidade uniforme a toda interface estimada, minimizando, simultaneamente em alguns pontos, os desajustes entre as profundidades conhecidas pelas sondagens e as estimadas nos mesmos pontos. O segundo método, denominado suavidade ponderada, estima as profundidades da interface em pontos discretos, admitindo o conhecimento a priori do contraste de densidade. Neste método, incorpora-se a informação geológica que a interface é suave, exceto em regiões de descontinuidades produzidas por falhas, ou seja, a interface é predominantemente suave porém localmente descontínua. Para a incorporação desta informação, desenvolvemos um processo iterativo em que três tipos de vínculos são impostos aos parâmetros: (a) ponderação da proximidade entre as profundidades estimadas em pontos adjacentes; (b) limites inferior e superior para as profundidades; e (c) proximidade entre todas as profundidades estimadas e um valor numérico conhecido. Inicializando com a solução estimada pelo método da suavidade global, este segundo método, iterativamente, acentua as feições geométricas presentes na solução inicial; ou seja, regiões suaves da interface tendem a tornar-se mais suaves e regiões abruptas tendem a tornar-se mais abruptas. Para tanto, este método atribui diferentes pesos ao vínculo de proximidade entre as profundidades adjacentes. Estes pesos são automaticamente atualizados de modo a acentuar as descontinuidades sutilmente detectadas pela solução da suavidade global. Os vínculos (b) e (c) são usados para compensar a perda da estabilidade, devida à introdução de pesos próximos a zero em alguns dos vínculos de proximidade entre parâmetros adjacentes, e incorporar a informação a priori que a região mais profunda da interface apresenta-se plana e horizontal. O vínculo (b) impõe, de modo estrito, que qualquer profundidade estimada é não negativa e menor que o valor de máxima profundidade da interface conhecido a priori; o vínculo (c) impõe que todas as profundidades estimadas são próximas a um valor que deliberadamente viola a profundidade máxima da interface. O compromisso entre os vínculos conflitantes (b) e (c) resulta na tendenciosidade da solução final em acentuar descontinuidades verticais e apresentar uma estimativa suave e achatada da região mais profunda. O terceiro método, denominado mínimo momento de inércia, estima os contrastes de densidade de uma região da subsuperfície discretizada em volumes elementares prismáticos. Este método incorpora a informação geológica que a interface a ser mapeada delimita uma fonte anômala que apresenta dimensões horizontais maiores que sua maior dimensão vertical, com bordas mergulhando verticalmente ou em direção ao centro de massa e que toda a massa (ou deficiência de massa) anômala está concentrada, de modo compacto, em torno de um nível de referência. Conceitualmente, estas informações são introduzidas pela minimização do momento de inércia das fontes em relação ao nível de referência conhecido a priori. Esta minimização é efetuada em um subespaço de parâmetros consistindo de fontes compactas e apresentando bordas mergulhando verticalmente ou em direção ao centro de massa. Efetivamente, estas informações são introduzidas através de um processo iterativo inicializando com uma solução cujo momento de inércia é próximo a zero, acrescentando, em cada iteração, uma contribuição com mínimo momento de inércia em relação ao nível de referência, de modo que a nova estimativa obedeça a limites mínimo e máximo do contraste de densidade, e minimize, simultaneamente, os desajustes entre os dados gravimétricos observados e ajustados. Adicionalmente, o processo iterativo tende a "congelar" as estimativas em um dos limites (mínimo ou máximo). O resultado final é uma fonte anômala compactada em torno do nível de referência cuja distribuição de constraste de densidade tende ao limite superior (em valor absoluto) estabelecido a priori. Estes três métodos foram aplicados a dados sintéticos e reais produzidos pelo relevo do embasamento de bacias sedimentares. A suavidade global produziu uma boa reconstrução do arcabouço de bacias que violam a condição de suavidade, tanto em dados sintéticos como em dados da Bacia do Recôncavo. Este método, apresenta a menor resolução quando comparado com os outros dois métodos. A suavidade ponderada produziu uma melhoria na resolução de relevos de embasamentos que apresentam falhamentos com grandes rejeitos e altos ângulos de mergulho, indicando uma grande potencialidade na interpretação do arcabouço de bacias extensionais, como mostramos em testes com dados sintéticos e dados do Steptoe Valley, Nevada, EUA, e da Bacia do Recôncavo. No método do mínimo momento de inércia, tomou-se como nível de referência o nível médio do terreno. As aplicações a dados sintéticos e às anomalias Bouguer do Graben de San Jacinto, California, EUA, e da Bacia do Recôncavo mostraram que, em comparação com os métodos da suavidade global e ponderada, este método estima com excelente resolução falhamentos com pequenos rejeitos sem impor a restrição da interface apresentar poucas descontinuidades locais, como no método da suavidade ponderada.