Low-income first time mothers: Effects on advanced practice nurse (APN) follow up telephone calls on maternal and infant health and health care charges

The United States has over 4 million births annually. Currently healthy women with non-complicated deliveries receive little to no routine postpartum support when discharged from the hospital. This is especially problematic if mothers are first time mothers, poor, have language barriers and little to no social support after giving birth. The purpose of this randomized clinical trial was to compare maternal and infant health outcomes, and health care charges between 2 groups of mothers and newborns. A control ( n = 69) group received routine posthospital discharge care. An intervention group (n = 70) received routine posthospital discharge care plus follow up telephone calls by advanced practice nurses (APNs) on days 3,7,14,21,28 and week 8. Both groups were followed for the first 8 weeks posthospital discharge following delivery to examine maternal health outcomes (perceived maternal stress, social support and perceived maternal physical health), infant health outcomes (routine medical follow up visits immunizations, weight gain), morbidity (urgent care visits, emergency room visits, rehospitalizations), health care charges (urgent care visits, emergency room visits, rehospitalizations) in both groups and charges for APN follow up in the intervention group only. Data were analyzed using descriptive statistics and two-sample t-tests. Study findings indicated that intervention group had significantly lower perceived maternal stress, significantly higher rating of perceived maternal health and higher levels of social support and by the end of the 2nd month posthospital discharge compared to control group mothers. Infants in the intervention group had: increased number of immunizations; fewer emergency room visits; and 1 infant rehospitalization compared to 3 infant rehospitalizations in the control group. The intervention groups' health care charges were significantly lower compared to the control group $14,333/$497 vs. $70,834/$1,068. These study results indicate that an intervention of APN follow up telephone calls in this sample of first time low-income culturally diverse mothers was an effective, safe, low cost, easy to apply intervention which improved mothers' and infants' health outcomes and reduced healthcare charges.

Energy-efficient self -organization of wireless acoustic sensor networks for ground target tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Development of New Structural Health Monitoring Techniques

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

Development of New Structural Health Monitoring Techniques

During the past two decades, many researchers have developed methods for the detection of structural defects at the early stages to operate the aerospace vehicles safely and to reduce the operating costs. The Surface Response to Excitation (SuRE) method is one of these approaches developed at FIU to reduce the cost and size of the equipment. The SuRE method excites the surface at a series of frequencies and monitors the propagation characteristics of the generated waves. The amplitude of the waves reaching to any point on the surface varies with frequency; however, it remains consistent as long as the integrity and strain distribution on the part is consistent. These spectral characteristics change when cracks develop or the strain distribution changes. The SHM methods may be used for many applications, from the detection of loose screws to the monitoring of manufacturing operations. A scanning laser vibrometer was used in this study to investigate the characteristics of the spectral changes at different points on the parts. The study started with detecting a load on a plate and estimating its location. The modifications on the part with manufacturing operations were detected and the Part-Based Manufacturing Process Performance Monitoring (PbPPM) method was developed. Hardware was prepared to demonstrate the feasibility of the proposed methods in real time. Using low-cost piezoelectric elements and the non-contact scanning laser vibrometer successfully, the data was collected for the SuRE and PbPPM methods. Locational force, loose bolts and material loss could be easily detected by comparing the spectral characteristics of the arriving waves. On-line methods used fast computational methods for estimating the spectrum and detecting the changing operational conditions from sum of the squares of the variations. Neural networks classified the spectrums when the desktop – DSP combination was used. The results demonstrated the feasibility of the SuRE and PbPPM methods.

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Analysis of the lateral diffuse metal-oxide semiconductor (LDMOS) power amplifier for cellular base stations

The primary purpose of this thesis was to present a theoretical large-signal analysis to study the power gain and efficiency of a microwave power amplifier for LS-band communications using software simulation. Power gain, efficiency, reliability, and stability are important characteristics in the power amplifier design process. These characteristics affect advance wireless systems, which require low-cost device amplification without sacrificing system performance. Large-signal modeling and input and output matching components are used for this thesis. Motorola's Electro Thermal LDMOS model is a new transistor model that includes self-heating affects and is capable of small-large signal simulations. It allows for most of the design considerations to be on stability, power gain, bandwidth, and DC requirements. The matching technique allows for the gain to be maximized at a specific target frequency. Calculations and simulations for the microwave power amplifier design were performed using Matlab and Microwave Office respectively. Microwave Office is the simulation software used in this thesis. The study demonstrated that Motorola's Electro Thermal LDMOS transistor in microwave power amplifier design process is a viable solution for common-source amplifier applications in high power base stations. The MET-LDMOS met the stability requirements for the specified frequency range without a stability-improvement model. The power gain of the amplifier circuit was improved through proper microwave matching design using input/output-matching techniques. The gain and efficiency of the amplifier improve approximately 4dB and 7.27% respectively. The gain value is roughly .89 dB higher than the maximum gain specified by the MRF21010 data sheet specifications. This work can lead to efficient modeling and development of high power LDMOS transistor implementations in commercial and industry applications.