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Flow measurement has always been one of the most critical processes in many industrial and clinical applications. The dynamic behavior of flow helps to define the state of a process. An industrial example would be that in an aircraft, where the rate of airflow passing the aircraft is used to

Flow measurement has always been one of the most critical processes in many industrial and clinical applications. The dynamic behavior of flow helps to define the state of a process. An industrial example would be that in an aircraft, where the rate of airflow passing the aircraft is used to determine the speed of the plane. A clinical example would be that the flow of a patient's breath which could help determine the state of the patient's lungs. This project is focused on the flow-meter that are used for airflow measurement in human lungs. In order to do these measurements, resistive-type flow-meters are commonly used in respiratory measurement systems. This method consists of passing the respiratory flow through a fluid resistive component, while measuring the resulting pressure drop, which is linearly related to volumetric flow rate. These types of flow-meters typically have a low frequency response but are adequate for most applications, including spirometry and respiration monitoring. In the case of lung parameter estimation methods, such as the Quick Obstruction Method, it becomes important to have a higher frequency response in the flow-meter so that the high frequency components in the flow are measurable. The following three types of flow-meters were: a. Capillary type b. Screen Pneumotach type c. Square Edge orifice type To measure the frequency response, a sinusoidal flow is generated with a small speaker and passed through the flow-meter that is connected to a large, rigid container. True flow is proportional to the derivative of the pressure inside the container. True flow is then compared with the measured flow, which is proportional to the pressure drop across the flow-meter. In order to do the characterization, two LabVIEW data acquisition programs have been developed, one for transducer calibration, and another one that records flow and pressure data for frequency response testing of the flow-meter. In addition, a model that explains the behavior exhibited by the flow-meter has been proposed and simulated. This model contains a fluid resistor and inductor in series. The final step in this project was to approximate the frequency response data to the developed model expressed as a transfer function.
ContributorsHu, Jianchen (Author) / Macia, Narciso (Thesis advisor) / Pollat, Scott (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2013
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Many tasks that humans do from day to day are taken for granted in term of appreciating their true complexity. Humans are the only species on the planet that have developed such an in-depth means of auditory communication. Recreating the mechanisms in the brain that recognize speech patterns is no

Many tasks that humans do from day to day are taken for granted in term of appreciating their true complexity. Humans are the only species on the planet that have developed such an in-depth means of auditory communication. Recreating the mechanisms in the brain that recognize speech patterns is no easy task. This paper compares and contrasts various algorithms used in modern day ASR systems, and focuses primarily on ASR systems in resource constrained environments. The Green colored blocks in Figure 1 will be focused on in greater detail throughout this paper, they are the key to building an exceptional ASR system. Deep Neural Networks (DNNs) are the clear and current leader among ASR technologies; all research in this field is currently revolving around this method. Although DNNs are very effective, many older methods of ASR are used often due to the complexities involved with DNNs; these difficulties include the large amount of hardware resources as well as development resources, such as engineers and money, required for this method.
ContributorsPetersen, Casey Alexander (Author) / Csavina, Kristine (Thesis director) / Pollat, Scott (Committee member) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
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The mental health of ASU students has been negatively affected by the pandemic. Our research looks to prove that COVID-19 has caused an increase in stress levels while uncovering other relationships to stress. We obtained our data by conducting a survey through Google Forms that was exclusively accessible to ASU

The mental health of ASU students has been negatively affected by the pandemic. Our research looks to prove that COVID-19 has caused an increase in stress levels while uncovering other relationships to stress. We obtained our data by conducting a survey through Google Forms that was exclusively accessible to ASU students. Stress levels were measured with the use of the Perceived Stress Scale (PSS). We find that the stress of ASU students from before the pandemic to during rises from 15 to 22 points, a 50% increase (n = 228). We discovered that women are more stressed than men before and during the pandemic. We also discovered that there is no difference between stresses among different races. We notice that there is a parabolic relationship between enrollment time and stress levels with the peak occurring during semesters 2-6. We also conclude that students who attended more than 5 events during the pandemic had lower stress scores, and those who had their videos on for at least 3 events had lower stress scores. Furthermore, students who utilized campus resources to manage their stress had higher stress levels than those who did not.

ContributorsRana, Mannat (Co-author) / Levine, Benjamin (Co-author) / Martin, Thomas (Thesis director) / Rendell, Dawn (Committee member) / College of Integrative Sciences and Arts (Contributor) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

The mental health of ASU students has been negatively affected by the pandemic. Our research looks to prove that COVID-19 has caused an increase in stress levels while uncovering other relationships to stress. We obtained our data by conducting a survey through Google Forms that was exclusively accessible to ASU

The mental health of ASU students has been negatively affected by the pandemic. Our research looks to prove that COVID-19 has caused an increase in stress levels while uncovering other relationships to stress. We obtained our data by conducting a survey through Google Forms that was exclusively accessible to ASU students. Stress levels were measured with the use of the Perceived Stress Scale (PSS). We find that the stress of ASU students from before the pandemic to during rises from 15 to 22 points, a 50% increase (n = 228). We discovered that women are more stressed than men before and during the pandemic. We also discovered that there is no difference between stresses among different races. We notice that there is a parabolic relationship between enrollment time and stress levels with the peak occurring during semesters 2-6. We also conclude that students who attended more than 5 events during the pandemic had lower stress scores, and those who had their videos on for at least 3 events had lower stress scores. Furthermore, students who utilized campus resources to manage their stress had higher stress levels than those who did not.

ContributorsRana, Mannat (Co-author) / Levine, Benjamin (Co-author) / Martin, Thomas (Thesis director) / Rendell, Dawn (Committee member) / College of Integrative Sciences and Arts (Contributor) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

The mental health of ASU students has been negatively affected by the pandemic. Our research looks to prove that COVID-19 has caused an increase in stress levels while uncovering other relationships to stress. We obtained our data by conducting a survey through Google Forms that was exclusively accessible to ASU

The mental health of ASU students has been negatively affected by the pandemic. Our research looks to prove that COVID-19 has caused an increase in stress levels while uncovering other relationships to stress. We obtained our data by conducting a survey through Google Forms that was exclusively accessible to ASU students. Stress levels were measured with the use of the Perceived Stress Scale (PSS). We find that the stress of ASU students from before the pandemic to during rises from 15 to 22 points, a 50% increase (n = 228). We discovered that women are more stressed than men before and during the pandemic. We also discovered that there is no difference between stresses among different races. We notice that there is a parabolic relationship between enrollment time and stress levels with the peak occurring during semesters 2-6. We also conclude that students who attended more than 5 events during the pandemic had lower stress scores, and those who had their videos on for at least 3 events had lower stress scores. Furthermore, students who utilized campus resources to manage their stress had higher stress levels than those who did not.

ContributorsLevine, Benjamin (Co-author) / Rana, Mannat (Co-author) / Martin, Thomas (Thesis director) / Rendell, Dawn (Committee member) / College of Integrative Sciences and Arts (Contributor) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05