Abstract Purpose Non-verbal utterances are an important tool of communication for individuals who are non- or minimally-speaking. While these utterances are typically understood by caregivers, they can be challenging to interpret by their larger community. To date, there has been little work done to detect and characterize the vocalizations produced by non- or minimally-speaking individuals. This paper aims to characterize five categories of utterances across a set of 7 non- or minimally-speaking individuals. Methods The characterization is accomplished using a correlation structure methodology, acting as a proxy measurement for motor coordination, to localize similarities and differences to specific speech production systems. Results We specifically find that frustrated and dysregulated utterances show similar correlation structure outputs, especially when compared to self-talk, request, and delighted utterances. We additionally witness higher complexity of coordination between articulatory and respiratory subsystems and lower complexity of coordination between laryngeal and respiratory subsystems in frustration and dysregulation as compared to self-talk, request, and delight. Finally, we observe lower complexity of coordination across all three speech subsystems in the request utterances as compared to self-talk and delight. Conclusion The insights from this work aid in understanding of the modifications made by non- or minimally-speaking individuals to accomplish specific goals in non-verbal communication.
This paper details a hybrid computational and analytical model to predict the performance of inline pressure-compensating (PC) drip irrigation emitters. The term inline refers to flow control devices mounted within the irrigation tubing. Pressure-compensating emitters deliver a relatively constant flow rate over a range applied pressure to accurately meter water to crops. Flow rate is controlled within the emitter by directing the water through a tortuous path (which imposes a fixed resistance), and then through a variable resistor composed of a flexible membrane that deflects under changes in pressure, restricting the flow path. An experimentally validated computational fluid dynamics (CFD) model was used to predict flow behavior through tortuous paths, and a pressure resistance parameter was derived to represent the pressure drop with a single variable. The bending and shearing mechanics of the membrane were modeled analytically and refined for accuracy by deriving a correction factor using finite element analysis. A least-squares matrix formulation that calculates the force applied by a line load of any shape, along which there is a prescribed deflection applied on a rectangular membrane, was derived and was found to be accurate to within one percent. The applicability of the assumption of locally fully developed flow through the pressure compensating chamber in a drip emitter was analyzed. The combined hybrid computational-analytical model reduces the computational time of modeling drip emitter performance from days to less than 30 minutes, dramatically lowering the time required to iterate and select optimal designs. The model was validated using three commercially available drip emitters, rated at 1.1, 2, and 3.8 L/hr. For each, the model predicted the flow rate with an error of twenty percent or less, as compared to the emitter performance published by the manufacturer.
Nonverbal vocalizations contain important affective and communicative information, especially for those who do not use traditional speech, including individuals who have autism and are non- or minimally verbal (nv/mv). Although these vocalizations are often understood by those who know them well, they can be challenging to understand for the community-at-large. This work presents (1) a methodology for collecting spontaneous vocalizations from nv/mv individuals in natural environments, with no researcher present, and personalized in-the-moment labels from a family member; (2) speaker-dependent classification of these real-world sounds for three nv/mv individuals; and (3) an interactive application to translate the nonverbal vocalizations in real time. Using support-vector machine and random forest models, we achieved speaker-dependent unweighted average recalls (UARs) of 0.75, 0.53, and 0.79 for the three individuals, respectively, with each model discriminating between 5 nonverbal vocalization classes. We also present first results for real-time binary classification of positive- and negative-affect nonverbal vocalizations, trained using a commercial wearable microphone and tested in real time using a smartphone. This work informs personalized machine learning methods for non-traditional communicators and advances real-world interactive augmentative technology for an underserved population.
Ocular prostheses are part of a substantial global market for ocular implants. However, demand for custom ocular prostheses (COPs) can outpace supply at clinics due to the slow pace of prosthesis manufacturing and limited supply of ocularists, particularly in emerging markets such as India. Existing manufacturing methods for COPs involve multiple stages of casting and molds with limited quality control, resulting in time-intensive trial and error with patients to achieve a comfortable fit. Through collaboration with the LV Prasad Eye Institute (LVPEI) in India, the authors improved manufacturing process efficiency for COPs and without significantly increasing cost or decreasing customizability. A time study of the current process showed that no single step was a dominant contributor to process time, necessitating a holistic change to the manufacturing process. The modified process uses dip coating of a 3D printed internal body made from a scanned impression. Based on a timed experimental trial, the modified process has a projected daily COP production rate increase of 100% compared to the existing process. A study of produced COP quality showed accumulated error of critical dimensions within reasonable limits, with the greatest error being less than 65% of maximum acceptable error.Note: no experiments on human or animal subjects were carried out in the writing of this paper.
Individuals who produce few spoken words ("minimally-speaking" individuals) often convey rich affective and communicative information through nonverbal vocalizations, such as grunts, yells, babbles, and monosyllabic expressions. Yet, little data exists on the affective content of the vocal expressions of this population. Here, we present 78,624 arousal and valence ratings of nonverbal vocalizations from the online ReCANVo (Real-World Communicative and Affective Nonverbal Vocalizations) database. This dataset contains over 7,000 vocalizations that have been labeled with their expressive functions (delight, frustration, etc.) from eight minimally-speaking individuals. Our results suggest that raters who have no knowledge of the context or meaning of a nonverbal vocalization are still able to detect arousal and valence differences between different types of vocalizations based on Likert-scale ratings. Moreover, these ratings are consistent with hypothesized arousal and valence rankings for the different vocalization types. Raters are also able to detect arousal and valence differences between different vocalization types within individual speakers. To our knowledge, this is the first large-scale analysis of affective content within nonverbal vocalizations from minimally verbal individuals. These results complement affective computing research of nonverbal vocalizations that occur within typical verbal speech (e.g., grunts, sighs) and serve as a foundation for further understanding of how humans perceive emotions in sounds.
Abstract Drip irrigation has the potential to help farmers increase crop production with lower on-farm water consumption than flood or sprinkler irrigation; yet, its high costs keep it out of reach for many smallholder farmers, who make up about 20 $$\%$$ % of the world’s population. Pressure-compensating (PC) drip emitters enable uniform water delivery to all crops in a field by regulating the emitter flow rate, but typically require high pumping pressures, contributing to high capital and operating costs for the pump and power system. Redesigning PC emitters for lower pressure operation could enable more energy-efficient and affordable drip systems. However, the current lack of published design theory for PC emitters hinders the development of emitters with desired hydraulic performance. To address this gap, we present an analytical, parametric model for the hydraulic behavior (i.e., the flow rate versus pressure curve) of inline PC emitters before the flow-regulating regime. We combine this model with a validated prototyping method to demonstrate its utility in the design of PC emitters with target activation pressures and flow rates, and demonstrate a sample design that achieves 38 $$\%$$ % lower activation pressure than commercial emitters with similar flow rates. The proposed model sheds light on the parametric relationships between PC emitter geometry and performance. It may inform R&D efforts in the irrigation industry and lead to improved emitter designs with low operating pressures, helping reduce drip system costs and increase access to drip irrigation among smallholder farmers.
The effect of chromium thickness on the barrier height of AuCr–nSi Schottky diodes and the current/voltage characteristics of AuCr–n–p+Si BARITT diodes is reported. The barrier height varies from 0.81 to 0.59 eV as the chromium thickness increases from zero (no chromium) to more than 200Å
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