Highly comparative feature-based time-series classification

A highly comparative, feature-based approach to time series classification is introduced that uses an extensive database of algorithms to extract thousands of interpretable features from time series. These features are derived from across the scientific time-series analysis literature, and include summaries of time series in terms of their correlation structure, distribution, entropy, stationarity, scaling properties, and fits to a range of time-series models. After computing thousands of features for each time series in a training set, those that are most informative of the class structure are selected using greedy forward feature selection with a linear classifier. The resulting feature-based classifiers automatically learn the differences between classes using a reduced number of time-series properties, and circumvent the need to calculate distances between time series. Representing time series in this way results in orders of magnitude of dimensionality reduction, allowing the method to perform well on very large datasets containing long time series or time series of different lengths. For many of the datasets studied, classification performance exceeded that of conventional instance-based classifiers, including one nearest neighbor classifiers using Euclidean distances and dynamic time warping and, most importantly, the features selected provide an understanding of the properties of the dataset, insight that can guide further scientific investigation

A pilot study of a text messaging intervention to modify illness and medication beliefs amongst patients diagnosed with inflammatory bowel disease

Intentional and unintentional medication non-adherence is a particular challenge for patients with inflammatory bowel disease (IBD). Non-adherence can affect patients’ quality of life, which can result in unfavorable treatment outcomes, more hospitalizations, and higher healthcare-related costs. The purpose of this study was to assess whether a tailored text message intervention designed to modify illness and medication adherence beliefs in patients with IBD would increase treatment compliance and change patients’ illness perceptions and medication concerns. This pilot study utilized a pre-test-post-test non-randomized design. A sample of 32 IBD patients was recruited within the UK. Participants’ medication beliefs and illness perception scores determined the set of tailored daily text messages, which were sent to patients over duration of 12 weeks. Medication adherence increased post-intervention, as “forgetting to take medication” decreased while “never” forgetting to take medication increased over time. A significant increase in treatment control and coherence and a decreased level of concern surrounding their condition was evident. Participants’ level of concern towards their medications changed during the 12 weeks, with a baseline mean concern score of 3.08 (.57) in comparison to the 12 weeks mean concern score of 2.89 (.59), which is statistically different, t (31) = 2.16, p < .038, r = .36 (medium effect). Sixty-six percent of participants from the baseline were aware of the necessity of their medication: “without my medication I would become ill.” The results have direct implications for improving medication adherence and changing illness and medication beliefs. This study validated the benefits of text messages and highlighted the importance of addressing these beliefs in order to understand the reasons for non-adherence fully

Output-based Aid for Sustainable Sanitation

A review of the experience to date in applying output-based and other results-oriented financing aid formats to the delivery of sanitation services and goods in developing countries. The paper looks at the theoretical underpinnings which justify output-based subsidies in sanitation, reviews a selection of output-based aid projects and then proposes some new approaches which could help to make financing in sanitation more effective and accountable

Development of Auditory Selective Attention: Why Children Struggle to Hear in Noisy Environments

Children’s hearing deteriorates markedly in the presence of unpredictable noise. To explore why, 187 school-age children (4–11 years) and 15 adults performed a tone-in-noise detection task, in which the masking noise varied randomly between every presentation. Selective attention was evaluated by measuring the degree to which listeners were influenced by (i.e., gave weight to) each spectral region of the stimulus. Psychometric fits were also used to estimate levels of internal noise and bias. Levels of masking were found to decrease with age, becoming adult-like by 9–11 years. This change was explained by improvements in selective attention alone, with older listeners better able to ignore noise similar in frequency to the target. Consistent with this, age-related differences in masking were abolished when the noise was made more distant in frequency to the target. This work offers novel evidence that improvements in selective attention are critical for the normal development of auditory judgments

Reduction of internal noise in auditory perceptual learning

This paper examines what mechanisms underlie auditory perceptual learning. Fifteen normal hearing adults performed two-alternative, forced choice, pure tone frequency discrimination for four sessions. External variability was introduced by adding a zero-mean Gaussian random variable to the frequency of each tone. Measures of internal noise, encoding efficiency, bias, and inattentiveness were derived using four methods (model fit, classification boundary, psychometric function, and double-pass consistency). The four methods gave convergent estimates of internal noise, which was found to decrease from 4.52 to 2.93 Hz with practice. No group-mean changes in encoding efficiency, bias, or inattentiveness were observed. It is concluded that learned improvements in frequency discrimination primarily reflect a reduction in internal noise. Data from highly experienced listeners and neural networks performing the same task are also reported. These results also indicated that auditory learning represents internal noise reduction, potentially through the re-weighting of frequency-specific channels

The Role of Response Bias in Perceptual Learning

Sensory judgments improve with practice. Such perceptual learning is often thought to reflect an increase in perceptual sensitivity. However, it may also represent a decrease in response bias, with unpracticed observers acting in part on a priori hunches rather than sensory evidence. To examine whether this is the case, 55 observers practiced making a basic auditory judgment (yes/no amplitude-modulation detection or forced-choice frequency/amplitude discrimination) over multiple days. With all tasks, bias was present initially, but decreased with practice. Notably, this was the case even on supposedly “bias-free,” 2-alternative forced-choice, tasks. In those tasks, observers did not favor the same response throughout (stationary bias), but did favor whichever response had been correct on previous trials (nonstationary bias). Means of correcting for bias are described. When applied, these showed that at least 13% of perceptual learning on a forced-choice task was due to reduction in bias. In other situations, changes in bias were shown to obscure the true extent of learning, with changes in estimated sensitivity increasing once bias was corrected for. The possible causes of bias and the implications for our understanding of perceptual learning are discussed

Learning to detect a tone in unpredictable noise

Eight normal-hearing listeners practiced a tone-detection task in which a 1-kHz target was masked by a spectrally unpredictable multitone complex. Consistent learning was observed, with mean masking decreasing by 6.4 dB over five sessions (4500 trials). Reverse-correlation was used to estimate how listeners weighted each spectral region. Weight-vectors approximated the ideal more closely after practice, indicating that listeners were learning to attend selectively to the task relevant information. Once changes in weights were accounted for, no changes in internal noise (psychometric slope) were observed. It is concluded that this task elicits robust learning, which can be understood primarily as improved selective attention

Development of pigments for thermal control coatings Final report, 17 Jun. - 16 Dec. 1965

Powdered metal oxide pigments by nucleation for temperature control coating