Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

The state of emergency management 2000: The process of emergency management professionalization in the United States and Florida

This dissertation analyzes the current status of emergency management professionalization in the United States and Florida using a qualitative case study. I investigate the efforts of various organizations at the national and state levels in the private and public sectors to organize emergency management as a profession. I conceptualize emergency management professionalization as occurring in two phases: the indirect institutionalization of the occupation of emergency management and the formal advancement toward an emergency management profession. The legislative, organizational, and procedural developments that occurred between approximately 1900 and the late 1970s became the indirect institutionalization of the occupation of emergency management. Over time, as our society developed and became increasingly complex, more disasters affect the security of the population. In order to adapt to increasing risks and vulnerabilities the emergency management system emerged and with it the necessary elements upon which a future profession could be established providing the basis for the formal advancement toward an emergency management profession. ^ During approximately the last twenty years, the formal advancement toward an emergency management profession has encompassed two primary strategies—certification and accreditation—motivated by the objective to organize a profession. Certification applies to individual emergency managers and includes all training and education. Accreditation of state and local emergency management agencies is reached by complying to a minimum level of proficiency with established standards of performance. Certification and accreditation are the mechanisms used to create an emergency management profession and thus act as axes around which the field of emergency management is organizing. ^ The purpose of this research is to provide a frame of reference for whether or not the field of emergency management is a profession. Based on sociology of professions literature, emergency management can be considered to be professionalizing. The current emergency management professionalization efforts may or may not be sufficient to achieve the ultimate goal of becoming a legitimate profession based on legal and public support for the exclusive right to perform emergency management tasks (monopoly) as well as self-regulation of those tasks (autonomy). ^

Medical advice, diabetes self-management, and health outcomes of a multi-ethnic population from the National Health and Nutrition Examination Survey 2007--2008

Diabetes self-management, an essential component of diabetes care, includes weight control practices and requires guidance from providers. Minorities are likely to have less access to quality health care than White non-Hispanics (WNH) (American College of Physicians-American Society of Internal Medicine, 2000). Medical advice received and understood may differ by race/ethnicity as a consequence of the patient-provider communication process; and, may affect diabetes self-management. ^ This study examined the relationships among participants’ report of: (1) medical advice given; (2) diabetes self-management, and; (3) health outcomes for Mexican-Americans (MA) and Black non-Hispanics (BNH) as compared to WNH (reference group) using data available through the National Health and Nutrition Examination Survey (NHANES) for the years 2007–2008. This study was a secondary, single point analysis. Approximately 30 datasets were merged; and, the quality and integrity was assured by analysis of frequency, range and quartiles. The subjects were extracted based on the following inclusion criteria: belonging to either the MA, BNH or WNH categories; 21 years or older; responded yes to being diagnosed with diabetes. A final sample size of 654 adults [MA (131); BNH (223); WNH (300)] was used for the analyses. The findings revealed significant statistical differences in medical advice reported given. BNH [OR = 1.83 (1.16, 2.88), p = 0.013] were more likely than WNH to report being told to reduce fat or calories. Similarly, BNH [OR = 2.84 (1.45, 5.59), p = 0.005] were more likely than WNH to report that they were told to increase their physical activity. Mexican-Americans were less likely to self-monitor their blood glucose than WNH [OR = 2.70 (1.66, 4.38), p<0.001]. There were differences among ethnicities for reporting receiving recent diabetes education. Black, non-Hispanics were twice as likely to report receiving diabetes education than WNH [OR = 2.29 (1.36, 3.85), p = 0.004]. Medical advice reported given and ethnicity/race, together, predicted several health outcomes. Having recent diabetes education increased the likelihood of performing several diabetes self-management behaviors, independent of race. ^ These findings indicate a need for patient-provider communication and care to be assessed for effectiveness and, the importance of ongoing diabetes education for persons with diabetes.^

Health changes in Hispanic older adults in a Spanish arthritis self -management education program

Arthritis is the most common chronic condition affecting older people and is a major cause of limited activity. Arthritis education programs in English have demonstrated a positive impact on health but these programs have not reached the Hispanic communities where arthritis is the leading cause of disability. Minorities, such as Hispanics, have traditionally been reluctant to pursue self-help programs, and have been identified as an under-served population in terms of medical care. This study examined the effectiveness of one community health adult education program targeting Hispanic older adults with arthritis, the Spanish Arthritis Self Management Education Program (SASMEP), by evaluating changes in the participants' general health, pain, disability, self-efficacy, health perceptions, frequency of physician visits, and exercise. A pre and post control group experimental design and analyses of covariance were used to determine the pre and post differences in health status and health behaviors for a group participating in the SASMEP and a group who did not using gender and age as covariates. A repeated measures design was also used, and repeated measures analyses of variance and post hoc tests were done on health status and health behavior data collected pre, post and one-year post education to determine long-term differences. ^ Results indicated the participants' health status significantly improved in general health, significantly decreased in pain, and significantly decreased in arthritic disability immediately following the education. Self-efficacy and health perceptions increased for both groups but not significantly. The participants' health behaviors showed significantly fewer physician visits and significantly increased time spent performing stretching and strengthening exercise and time spent performing aerobic exercise. No group differences were found in the frequency of arthritis physician visits. ^ The improvements seen immediately after the SASMEP participation were not reflected in the post one-year scores. No significant differences were found for the participants' health status or health behaviors one year following the education. Health status and health behaviors did not return below baseline scores after one year suggesting the participants' health, although not improved, did not deteriorate. Therefore, the SASMEP education provided short-term health benefits for older Hispanic adults with arthritis, but not long-term health benefits. ^

Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^

Diabetes Self Management: Are Cuban Americans Receiving Quality Health Care?

Objectives: We investigated the relationship among factors predicting inadequate glucose control among 182 Cuban-American adults (Females=110, Males=72) with type 2 diabetes mellitus (CAA). Study Design: Cross-sectional study of CAA from a randomized mailing list in two counties of South Florida Methods: Fasted blood parameters and anthropometric measures were collected during the study. BMI was calculated (kg/ m2). Characteristics and diabetes care of CAA were self-reported Participants were screened by trained interviewers for heritage and diabetes status (inclusion criteria: self-reported having type 2 diabetes; age  35 years, male and female; not pregnant or lactating; no thyroid disorders; no major psychiatric disorders). Participants signed informed consent form. Statistical analyses used SPSS and included descriptive statistic, multiple logistic and ordinal logistic regression models, where all CI 95%. Results: Eighty-eight percent of CAA had BMI of ≥ 25 kg/ m2. Only 54% reported having a diet prescribed/told to schedule meals. We found CAA told to schedule meals were 3.62 more likely to plan meals (1.81, 7.26), p<0.001) and given a prescribed diet, controlling for age, corresponded with following a meal plan OR 4.43 (2.52, 7.79, p<0.001). The overall relationship for HbA1c < 8.5 to following a meal plan was OR 9.34 (2.84, 30.7. p<0.001). Conclusions: The advantage of having a medical professional prescribe a diet seems to be an important environmental support factor in this sample’s diabetes care, since obesity rates are well above the national average. Nearly half CAA are not given dietary guidance, yet our results indicate CAA may improve glycemic control by receiving dietary instructions.

Diabetes Self-management Behaviors, Medical Care, Glycemic Control, and Self-rated Health in US Men by Race/Ethnicity

Men, particularly minorities, have higher rates of diabetes as compared with their counterparts. Ongoing diabetes self-management education and support by specialists are essential components to prevent the risk of complications such as kidney disease, cardiovascular diseases, and neurological impairments. Diabetes self-management behaviors, in particular, as diet and physical activity, have been associated with glycemic control in the literature. Recommended medical care for diabetes may differ by race/ethnicity. This study examined data from the National Health and Nutrition Examination Surveys, 2007 to 2010 for men with diabetes (N = 646) from four racial/ethnic groups: Mexican Americans, other Hispanics, non-Hispanic Blacks, and non-Hispanic Whites. Men with adequate dietary fiber intake had higher odds of glycemic control (odds ratio = 4.31, confidence interval [1.82, 10.20]), independent of race/ethnicity. There were racial/ethnic differences in reporting seeing a diabetes specialist. Non-Hispanic Blacks had the highest odds of reporting ever seeing a diabetes specialist (84.9%) followed by White non-Hispanics (74.7%), whereas Hispanics reported the lowest proportions (55.2% Mexican Americans and 62.1% other Hispanics). Men seeing a diabetes specialist had the lowest odds of glycemic control (odds ratio = 0.54, confidence interval [0.30, 0.96]). The results of this study suggest that diabetes education counseling may be selectively given to patients who are not in glycemic control. These findings indicate the need for examining referral systems and quality of diabetes care. Future studies should assess the effectiveness of patient-centered medical care provided by a diabetes specialist with consideration of sociodemographics, in particular, race/ethnicity and gender.

Statistical Dialog Management for Health Interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.