University of Maryland, Baltimore County
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A Camera-based Fluorescence-dependent Temperature Sensor for Neonatal Care
No full textThere are many examples of wireless non-contact temperature measurement systems out there but most of them are work at high temperatures or do not have sufficient resolution for use in the physiological domain (30�C-42�C). Even to this date, temperature measurement in incubators is done by attaching thermistor probes to the skin of the baby. This thesis presents a non-contact temperature measurement system designed for neonatal care. The system removes the need of attaching thermistor probes to the neonate's skin and therefore reduces the risk of epidermal stripping, microbial infections, etc. The fluorescence intensity ratio (ratiometric) technique is utilized to determine the temperature of a target using temperature responsive fluorophores. This technique measures the changes in the fluorescence intensity as the temperature is changed. The ratiometric technique utilizes two separate fluorophores where one is non-sensitive to temperature and thus serves as a reference. Determining results using ratiometric techniques also minimizes changes in the final measurements when environmental changes such as changes in ambient lights occur. An illuminator is employed to excite the fluorophores which then emit fluorescence that is measured by a camera. This is done by capturing consecutive frames with the illuminator on and then off and then subtracting them. The data is captured, stored, pre-processed and sent to the computer using an FPGA. The MATLAB computational environment is utilized to carry out final processing and display of the ratiometric values. The thesis looks into variable situational changes that can present themselves during actual application of the system and studies the effect on the stability of the ratiometric fluorescence measured. Measurements of the ratiometric fluorescence under different conditions suggest that a low-cost sensing system is viable. The resolution of the system is reported to be better than 0.18˚C
Biospecimen Assessment
No full textBiomaker evaluation has become a very important topic as epidemiologic studies increasingly depend on biomarkers to indicate exposure. In this dissertation, we contribute to the literature of biomaker assessment in two ways. First we consider pooling strategies for biomarker assessment. Pooling physically mixes two or more individual biospecimens and obtains a single biomarker measurement, thus reducing cost and the quantity of biospecimen required from each individual. Reducing cost without compromising power or efficiency may allow prohibitively expensive and very important hypotheses to be explored. For example, a pooling design that pools individuals in pairs will halve the costs associated with biomarker assessment. A particularly important hypothesis in studying complex diseases such as infertility, cancer, heart disease, and obesity is the gene-environment interaction. In this dissertation we propose novel pooling strategies for very inexpensive and efficient estimates of gene-environment interactions. Furthermore, we use the estimation maximization (EM) algorithm to estimate interaction effects of a logistic model when continuous biomarkers are measured in pools. Use of the EM algorithm when biomarkers are measured for pools rather than for each individual is an important and natural extension to the pooling literature. Second, we contribute to statistical methods for effectively incorporating known biological constraints in analyses of reproductive hormonal patterns during the menstrual cycle. Incorporating known biological constraints is important for proper statistical inference and it may increase model efficiency
Using Mobile Data Collectors to Federate Clusters of Disjoint Sensor Network Segments
No full textWireless Sensor Networks (WSN) operating unattended in harsh environments have the higher probability of suffering from large scale damage, where many nodes fail simultaneously and the network gets partitioned into several disjoint segments. Restoring connectivity of structurally damaged WSN's segments may be very urgent considering that they are employed to assist in risky missions. A similar scenario is when multiple standalone networks are to be federated to serve an emerging event such as an earthquake and conduct search-and-rescue. To deal with these scenarios, Mobile Data Mules (MDMs) are employed to establish intermittent links by moving around and carrying data from one segment to another. To limit data delivery latency and minimize the motion overhead, the travel path of the MDM should be shortened. When the availability of MDMs is not an issue, a minimum spanning tree of the segment is formed and one MDM is assigned to serve each link on the tree, i.e., a total of (N-1) mules are involved where N is the number of segments. In this thesis, we study a constrained version of the federation problem when the number of MDM's k is less than (N-1), which makes the problem more challenging. We present a novel algorithm that groups the segments into k overlapping clusters based on the inter-segment proximity. Each cluster is assigned a distinct MDM to tour its segments. A segment that belongs to two clusters serves as a gateway that enables data transfer across clusters. Our algorithm minimizes the tour length for each MDM and sets the speed of the individual MDMs to rendezvous at the gateway nodes so that buffering space and time for inter-cluster traffic are minimized. The simulation results confirm the effectiveness of our algorithm
The Immigration Experiences, Acculturation, and Parenting of Chinese Immigrant Mothers
No full textThe overall goal of the present study was to examine Chinese immigrant mothers' reasons for migration, experiences of migrating to the U.S., their acculturation strategies, adjustment, and parenting through a complementarity mixed-method approach. Both quantitative and qualitative methodologies were utilized concurrently to address the overall aim of this cross-sectional study. Specifically, the sample for the quantitative approach comprised 119 first-generation Chinese immigrant mothers of young children in Maryland. Utilizing data obtained through questionnaires, Chinese immigrant mothers were grouped into four different acculturation strategies (integration, assimilation, separation, and marginalization) and compared on: (1) their reasons for migration; (2) the role of negative and positive factors in their acculturation strategies; (3) their psychological functioning; and (4) their parenting styles. To complement and add to the findings obtained through the quantitative approach, 50 of the 119 mothers were interviewed using a qualitative approach. The themes raised by these Chinese immigrant mothers during semi-structured interviews regarding their: (1) reasons for migration and pre-migration expectations; (2) negative and positive immigration experiences; (3) evaluations of their immigration decision; and (4) conceptualization of Chinese and American parenting and changes in their parenting since they migrated to the U.S., were analyzed. This complementarity mixed-method approach allowed for an enriched, elaborated understanding of the immigration experiences, acculturation, parenting, and adjustment of Chinese immigrant mothers. The findings of the present study can provide important information to guide culturally informed community resources and policy development to support the adaptive transition and healthy development of Chinese immigrant families with young children in the context of small co-ethnic communities
Predicting the Activities of Mobile Phone Users with Hidden Markov Models
No full textMobile phones are ubiquitous and increasingly capable, with sophisticated sensors, network access, significant storage and processing power and access to a wide range of application data. They can improve the range and quality of their services by acquiring and using models of their context, including the activities in which their users are engaged. This thesis explores the use of supervised machine learning techniques for predicting a Smartphone user's activities from available sensor data. We have specifically concentrated on applying classifiers and ensembles using hidden markov models for activity recognition. Our classifiers predict a user's current activity from among a set of conceptual activity classes such as sleeping, traveling, playing, working, and chatting/watching TV. We have experimented with and evaluated the effectiveness of different approaches on data collected on Android Smartphone by university faculty and students
Expectancies and Motives as Mediating Links between College Students' Personality and Alcohol Use
No full textPersonality, alcohol expectancies, and drinking motives have been identified as key factors affecting alcohol use and drinking patterns in college populations (Cooper et al., 2000; Katz et al., 2000; Kuntsche et al., 2008). To date, most research has focused on the mediating effects of motives to drink, rather than expectancies of drinking, on the relation between personality and alcohol use. The current study examined the mediating effects of both alcohol expectancies and motives on the relation between personality and alcohol use, specifically looking at the strength of these mediating variables in a sample of full-time college students. Two-hundred and seventy five undergraduate students completed an online questionnaire assessing personality (extraversion and neuroticism), alcohol expectancies (positive and negative), drinking motives (enhancement, coping, and social), and patterns of alcohol use (frequency and intensity). Results found small-to-moderate relations among study variables, with limited mediating effects of expectancies and motives
Self-Efficacy as a Mediator of Impulsivity in the Prediction of Drinking and Drinking Consequences During Treatment in Alcohol-Dependent Individuals
No full textMany factors, including facets of personality, contribute to alcohol-dependent individuals' ability to achieve and maintain abstinence during treatment. This study examined the relation between trait impulsivity and abstinence self-efficacy in the prediction of drinking outcomes in two subsamples of Project MATCH participants who drank during 12 weeks of outpatient treatment: 1) individuals struggling to sustain sobriety following inpatient treatment, and 2) individuals trying to achieve sobriety after entering outpatient treatment directly. Multiple linear regression was used to test three models during treatment in which self-efficacy mediated impulsivity's prediction of 1) the intensity of drinking, 2) the total number of drinks consumed, and 3) the associated consequences of drinking. None of the regression analyses yielded significant relations among the variables and mediation was not supported in any of the models. Possible reasons include issues with sample characteristics, measurement limitations, the reduction of the Project MATCH sample, and the models' underlying assumptions
Differences in Depressive Symptoms Among African Americans and Whites: Prevalence, Symptom Patterns and Coping Resources
No full textRacial differences in self-reported depressive symptomatology have been inconsistent. The current study examined potential interactive relations of race (Black and White) and SES (i.e., poverty status) to the magnitude and patterns of depressive symptoms with adjustment for potentially important confounding variables. Also examined were racial differences in the use of culturally-relevant coping resources, and whether these coping resources were differentially protective against depression in Blacks and Whites. Participants were 2,440 socioeconomically diverse men and women drawn from the Healthy Aging in Neighborhoods of Disparities across the Life Span (HANDLS) study (58% Black) had completed the Center for Epidemiologic Studies - Depression scale (CES-D). After covariate adjustment, multiple regression analyses revealed no significant interactions of race and poverty status, or main effects of race with respect to depressive symptoms. However, participants living in poverty displayed significantly higher levels of depressive symptoms, and clinically significant depression, than those above the poverty line (p's < .05); these findings were only apparent in women in exploratory analyses. No significant associations were noted for race or the interaction of race and poverty status for the depressive affect, somatic complaints, or interpersonal problems subscales of the CES-D. However, Black participants reported significantly higher levels of positive affect than Whites (p < .05), but in women only. Additionally, participants living in poverty reported significantly higher levels of somatic complaints and depressive affect and less positive affect than those above the poverty line (p's < .05). Blacks reported significantly higher levels of social support, religious coping and ethnic identity than Whites (p's < .05). Participants living in poverty reported less emotional support and religious coping than those above the poverty line (p's < .05). However, coping resources did not moderate the relations of race to depressive symptoms. Exploratory analyses revealed that non-poverty Blacks who reported greater ethnic identity scores had fewer depressive symptoms. Results suggest complex associations among race, poverty status, and sex with respect to depressive symptoms and relevant coping resources. Poverty status may confer risk for depressive symptoms among women. Findings may point to the potential for positive adaptation among African Americans, particularly women
