A Logical Approach to Reasoning by Analogy

We analyze the logical form of the domain knowledge that grounds analogical inferences and generalizations from a single instance. The form of the assumptions which justify analogies is given schematically as the "determination rule", so called because it expresses the relation of one set of variables determining the values of another set. The determination relation is a logical generalization of the different types of dependency relations defined in database theory. Specifically, we define determination as a relation between schemata of first order logic that have two kinds of free variables: (1) object variables and (2) what we call "polar" variables, which hold the place of truth values. Determination rules facilitate sound rule inference and valid conclusions projected by analogy from single instances, without implying what the conclusion should be prior to an inspection of the instance. They also provide a way to specify what information is sufficiently relevant to decide a question, prior to knowledge of the answer to the question

Dark-Ages Reionisation & Galaxy Formation Simulation XVI: The Thermal Memory of Reionisation

Intergalactic medium temperature is a powerful probe of the epoch of reionisation, as information is retained long after reionisation itself. However, mean temperatures are highly degenerate with the timing of reionisation, with the amount heat injected during the epoch, and with the subsequent cooling rates. We post-process a suite of semi-analytic galaxy formation models to characterise how different thermal statistics of the intergalactic medium can be used to constrain reionisation. Temperature is highly correlated with redshift of reionisation for a period of time after the gas is heated. However as the gas cools, thermal memory of reionisation is lost, and a power-law temperature-density relation is formed, $T = T_0(1+\delta)^{1-\gamma}$ with $\gamma \approx 1.5$. Constraining our model against observations of electron optical depth and temperature at mean density, we find that reionisation likely finished at $z_{\rm{reion}} = 6.8 ^{+ 0.5} _{-0.8}$ with a soft spectral slope of $\alpha = 2.8 ^{+ 1.2} _{-1.0}$. By restricting spectral slope to the range $[0.5,2.5]$ motivated by population II synthesis models, reionisation timing is further constrained to $z_{\rm{reion}} = 6.9 ^{+ 0.4} _{-0.5}$. We find that, in the future, the degeneracies between reionisation timing and background spectrum can be broken using the scatter in temperatures and integrated thermal history.Comment: 17 pages, 17 figures, Accepted for publication in MNRA

Coordination of Foliar and Wood Anatomical Traits Contributes to Tropical Tree Distributions and Productivity along the Malay-Thai Peninsula

Drought is a critical factor in plant species distributions. Much research points to its relevance even in moist tropical regions. Recent studies have begun to elucidate mechanisms underlying the distributions of tropical tree species with respect to drought; however, how such desiccation tolerance mechanisms correspond with the coordination of hydraulic and photosynthetic traits in determining species distributions with respect to rainfall seasonality deserves attention. In the present study, we used a common garden approach to quantify inherent differences in wood anatomical and foliar physiological traits in 21 tropical tree species with either widespread (occupying both seasonal and aseasonal climates) or southern (restricted to aseasonal forests) distributions with respect to rainfall seasonality. Use of congeneric species pairs and phylogenetically independent contrast analyses allowed examination of this question in a phylogenetic framework. Widespread species opted for wood traits that provide biomechanical support and prevent xylem cavitation and showed associated reductions in canopy productivity and consequently growth rates compared with southern species. These data support the hypothesis that species having broader distributions with respect to climatic variability will be characterized by traits conducive to abiotic stress tolerance. This study highlights the importance of the well-established performance vs. stress tolerance trade-off as a contributor to species distributions at larger scales

Sound Quality Evaluation of Refrigerated Truck Noise

Noise from refrigeration units on trucks can be a problem, particularly when the trucks are parked near residences. The development of a sound evaluation method that takes into account the strength of all sound attributes affecting people’s responses, including level, is described here. Such a model, coupled with a sound prediction methodology, would be helpful to unit designers who are concerned with optimizing a unit’s acoustical performance. The analysis of human subject responses to a variety of refrigerated truck sounds (in the third of a series of three subjective tests) is described. Sixty participants rated 25 recorded and digitally modified refrigerated truck sounds as well as 25 residential HVAC equipment sounds. Fourteen sound quality metrics were evaluated as potential variables in a model to predict the average annoyance ratings of the refrigerated truck sounds. A rate-change-of-level metric that captured the impulsive character of the refrigerated truck unit noise was developed, and the best performing model comprised it, a level metric and a spectral balance metric. The performance of the model when used with signals and ratings taken from other tests is described

Descriptors of Sound from HVAC&R Equipment

A test was conducted to investigate how people describe HVAC&R equipment noise. Twenty-eight recordings and modified recordings were played to 42 subjects who wrote down descriptions as they heard the sounds. Subjects also rated these and 12 other sounds on an annoyance scale. The words used by subjects were categorized into 9 groups and the occurrences of the words within a group were counted for each sound. The results of the word analysis were compared to results of a sound quality metric analysis of the sounds, and to the results of the annoyance test. There was a high degree of correlation between the word scores and the corresponding metric values. The performance of linear models of metrics as predictors of annoyance was examined and loudness was the strongest contributor because of the large range of loudness used in the test. There were two significant outliers to the general trend of the predictions; these were sounds that were described by subjects as “sharp” and “high pitched”. The results of this test are being used in the design of a semantic differential test to examine the relationship between sound characteristics and annoyance further

Results of a Semantic Differential Test to Evaluate HVAC&R Equipment Noise

HVAC and Refrigeration (HVAC&R) equipment designers would like to have better noise criteria to guide their designs to reduce customer complaints and to understand what characteristics of sounds people dislike. To develop a robust sound evaluation model, the main sound characteristics that influence overall judgments of the sounds need to be determined. A semantic differential test was conducted using twenty-two sounds that were a mixture of recordings and modified recordings of two types of HVAC&R units. Sound descriptions provided by subjects in another test were used to develop seventeen rating scales. A factor analysis was performed on the ratings of thirty-nine subjects with normal hearing. Three strong factors were identified that are related to loudness, tonal content or sharpness, and fluctuation or irregularity. The correlation between sound metrics and average responses on each scale was examined. The highest correlations were always for the metric that is supposed to measuring the attribute associated with a particular rating scale. Models to predict annoyance ratings from sound metrics were also examined, and models that included a loudness and sharpness term gave very good results, but these need further development and need to be tested on a greater variety of HVAC&R sounds. The results of this test have also inspired development of signal modification techniques to separate tonality and sharpness attributes so that their individual influences on overall judgments of the sounds can be examined

The Design and Evaluation of Microphone Arrays for the Visualization of Noise Sources on Moving Vehicles

The present work was directed towards the design of a sideline microphone array specifically adapted to the visualization of automotive noise sources in the 500 Hz to 2000 Hz range. The particular design philosophy followed here involved the minimization of the array redundancy: i.e., the minimization of the number of pairs of microphones that are separated by the same distance in the same directions. The performance of sixty-four element microphone arrays designed according to this principle will be illustrated through the use of simulated motor vehicle passbys. In addition, their performance will be compared with more conventional array designs: e.g., elliptical, and spiral arrays

Sound Quality Evaluation of Residential HVAC&R Equipment

HVAC and Refrigeration (HVAC&R) equipment designers would benefit if there were better noise criteria for optimization of noise control treatments. Development of a model that can predict the average annoyance ratings of residential HVAC&R equipment sound is described. Three sets of subjective tests were performed, and the results from part of the third test are described. Three rating exercises were designed for the 60 subjects who participated. In each of the three parts the 50 sounds were a mixture of recordings and recordings that were digitally modified to decrease the correlation between sound metrics. In Part A the sounds tended to be louder, in Part B quieter sounds were rated and in Part C the sounds covered a wider range of loudness, similar to that used in the previous two tests. Thirteen sound quality metrics were tested as parameters in a linear model that predicts average annoyance ratings. The best performing model contained a tone-adjusted level, a spectral balance, a tonality and a roughness metric. The model was also used to predict average annoyance ratings in previously conducted tests and R2 values ranged from 0.90 to 0.94. Ongoing work includes examination of model deficiencies to identify potential sound attribute levels that cause actual ratings to be higher than those predicted

Perception of Diesel Engine Gear Rattle Noise

Component sound quality is an important factor in the design of competitive diesel engines. One component noise that causes complaints is the gear rattle that originates in the front-of-engine gear train which drives the fuel pump and other accessories. The rattle is caused by repeated tooth impacts resulting from fluctuations in differential torsional acceleration of the driving gears. These impacts generate a broadband, impulsive noise that is often perceived as annoying. In most previous work, the overall sound quality of diesel engines has been considered without specifically focusing on predicting the perception of gear rattle. Gear rattle level has been quantified based on angular acceleration measurements, but those measurements can be difficult to perform. Here, the emphasis was on developing a metric based on subjective testing of the perception of gear rattle. In the first part of the present work, a method to simulate gear rattle noise and incorporate it into a no-gear-rattle (baseline) recording was developed. That procedure enabled controlled variation of rattle within the total engine noise signal. The simulations were then used in a psychoacoustic test that was designed to quantify detectable levels, perception of growth, and increase in annoyance due to the presence of gear rattle noise. Forty subjects participated in the threshold detection tests and a paired comparison annoyance test. The responses of people who reported having experience with diesel engines were compared to those of a more general population. The subjects with diesel engine experience were found to be better at detecting gear rattle noise and found rattle more annoying than the other subjects, particularly at high rattle levels. Current work is focused on development of metrics that accurately reflect human responses to gear rattle