A high efficient biometrics approach for unconstrained iris segmentation and recognition

This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated at 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at 97% in a Noisy Iris Challenge Evaluation (NICE.I) in an international competition that involved 97 participants worldwide involving 35 countries, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time. The second part of this dissertation presents an innovative segmentation and recognition approach using video-based iris images. Following the segmentation stage which delineates the iris region through a novel segmentation strategy, some pioneering experiments on the recognition stage of the less-constrained video iris biometrics have been accomplished. In the video-based and less-constrained iris recognition, the test or subject iris videos/images and the enrolled iris images are acquired with different acquisition systems. In the matching step, the verification/identification result was accomplished by comparing the similarity distance of encoded signature from test images with each of the signature dataset from the enrolled iris images. With the improvements gained, the results proved to be highly accurate under the unconstrained environment which is more challenging. This has led to a false acceptance rate (FAR) of 0% and a false rejection rate (FRR) of 17.64% for 85 tested users with 305 test images from the video, which shows great promise and high practical implications for iris biometrics research and system design.

Positron emission tomography (PET) tumor segmentation and quantification: Development of new algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera's point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ∼10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera's PSF. The algorithm can also improve dose estimation and treatment planning.^

Positron Emission Tomography (PET) Tumor Segmentation and Quantification: Development of New Algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera’s point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ~10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera’s PSF. The algorithm can also improve dose estimation and treatment planning.

Host and network optimizations for performance enhancement and energy efficiency in data center networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.

Supplemental instruction, study habits, and the community college student

The purpose of this study was to demonstrate if the academic assistance program Supplemental Instruction (SI) facilitates the acquisition of effective study behaviors through strategies that transcend simple double-exposure to the course material. Its advocates claim it increases academic achievement using learner-centered knowledge and acquisition of effective study behaviors. SI sessions are specifically related to particular courses that students are taking. Sessions are facilitated by the SI leader who has taken the subject matter course in the past. Students review the content of the previous subject matter class using collaborative learning strategies coordinated by a SI leader. In addition, the SI leader models appropriate study behaviors in his or her interactions with the students. ^ An instructor at a large Florida community college who taught five classes of an Anatomy & Physiology I course (traditionally supported by SI) was identified. Two of the classes were randomly selected to participate in SI activities, and two classes were random chosen to participate in alternate, computer-based activities that dealt with the course content, but did not include work in developing students' study behaviors. These treatments were carried out over the course of an entire semester. Participation was mandatory. ^ Data were collected on two variables. Academic achievement in anatomy and physiology content was measured both pre- and post-treatment using an instructor developed examination. Student study behaviors were measured using pre- and post-treatment administration of the Study Behavior Inventory, a valid and reliable instrument that provides scores on three categories of study behaviors: (a) Academic self-efficacy, (b) Preparation for routine academic tasks, and (c) Preparation for long range academic tasks. Measures obtained at the end of the semester of treatment revealed no significant differences between the SI and alternative treatment groups in post-treatment achievement test score and the post-treatment scores on the three study behaviors categories when adjusted for pre-treatment scores. ^ These results suggest that the development of appropriate study behaviors requires more time than SI, as it is now implemented, can provide. In addition, results indicate that improved academic achievement may be attained through any number of means that include repeated exposure to course material. ^

Advances in Hospitality Education: Courseware, Audiographics, and Cyberspace

Technology will play an increasingly larger role in the education of students within the hospitality curriculum. There are a significant number of emerging educational technologies aimed at changing the delivery of the entire curriculum. The development of technological platforms for multimedia instructional courseware, distance learning through audiographics, and virtual reality simulation are expected to alter and enhance the learning process while extending the boundaries of the traditional hospitality classroom.

Multimedia Training: Why Some use it and Some Do Not

Forms of interactive multimedia, including CD-ROM, DV-I, Laserdisc, and virtual reality, have given a new perspective to training in many industries. As the hospitality industry and other service industries continue to grow, these forms of technology are becoming of increasing interest as organizations strive to deliver more efficient and effective services to customers and employees

Resistance Performances: (Re)constructing Spaces of Resistance and Contention in the 2010-2011 University of Puerto Rico Student Movement

On the night of April 20, 2010, a group of students from the University of Puerto Rico (UPR), Río Piedras campus, met to organize an indefinite strike that quickly broadened into a defense of accessible public higher education of excellence as a fundamental right and not a privilege. Although the history of student activism in the UPR can be traced back to the early 1900s, the 2010-2011 strike will be remembered for the student activists’ use of new media technologies as resources that rapidly prompted and aided the numerous protests. This activist research entailed a critical ethnography and a critical discourse analysis (CDA) of traditional and alternative media coverage and treatment during the 2010 -2011 UPR student strike. I examined the use of the 2010-2011 UPR student activists’ resistance performances in constructing local, corporeal, and virtual spaces of resistance and contention during their movement. In particular, I analyzed the different tactics and strategies of resistance or repertoire of collective actions that student activists used (e.g. new media technologies) to frame their collective identities via alternative news media’s (re)presentation of the strike, while juxtaposing the university administration’s counter-resistance performances in counter-framing the student activists’ collective identity via traditional news media representations of the strike. I illustrated how both traditional and alternative media (re)presentations of student activism developed, maintained, and/or modified students activists’ collective identities. As such, the UPR student activism’s success should not be measured by the sum of demands granted, but by the sense of community achieved and the establishment of networks that continue to create resistance and change. These networks add to the debate surrounding Internet activism and its impact on student activism. Ultimately, the results of this study highlight the important role student movements have had in challenging different types of government policies and raising awareness of the importance of an accessible public higher education of excellence.

Menopause, rurlity, and obesity in rural African American women

In the US, one in every eight deaths is due to an obesity-related chronic health condition (ORCHC). More than half of African American women (AAW) 20 years old or older are obese or morbidly obese, as are 63% of menopausal AAW. Many have ORCHC that increase their morbidity and mortality and increase health care costs. In 2013, 42.6 percent of AAs living in South Carolina (SC) were obese. The purpose of this cross-sectional study was to identify the cognitive, behavioral, biological, and demographic factors that influence health outcomes (BMI, and ORCHC) of AAW living in rural SC. A sample of 200 AAW (50 in each of the 4 groups of rurality by menopausal status), 18-64 years, completed the: Menopausal Rating Scale (symptoms); Body Image Assessment for Obesity (self-perception of body); Mental Health Inventory; Block Food Frequency Questionnaire; Eating Behaviors and Chronic Conditions, Traditional Food Habits, and Food Preparation Technique questionnaires — and measures for Body Mass Index. Most rural, and premenopausal AAW were single and not living with a partner. Premenopausal women had significantly higher educational levels. Sixty percent of AAW had between 1 and 5 ORCHC. Most AAW used salt based seasonings, ate deep fried foods 1 to 3 times a week, and ate outside the home 1 to 3 times a month. Few AAW knew the correct daily serving for grains and dairy, and most consumed less than the recommended daily serving of fruits, vegetables and dairy. Morbidly obese AAW used more traditional food preparation techniques than obese and normal-weight AAW. Rural, and menopausal AAW had significantly higher morbid obesity levels, consumed larger portions of meats and vegetables, and reported more body image dissatisfaction than very rural AAW, and premenopausal AAW, respectively. Controlling for socioeconomic factors the relationships between perceptions of body images, psychological distress, and psychological wellbeing remained significant for numbers of ORCHC^

Menopause, Rurality, And Obesity in Rural African American Women

In the US, one in every eight deaths is due to an obesity-related chronic health condition (ORCHC). More than half of African American women (AAW) 20 years old or older are obese or morbidly obese, as are 63% of menopausal AAW. Many have ORCHC that increase their morbidity and mortality and increase health care costs. In 2013, 42.6 percent of AAs living in South Carolina (SC) were obese. The purpose of this cross-sectional study was to identify the cognitive, behavioral, biological, and demographic factors that influence health outcomes (BMI, and ORCHC) of AAW living in rural SC. A sample of 200 AAW (50 in each of the 4 groups of rurality by menopausal status), 18-64 years, completed the: Menopausal Rating Scale (symptoms); Body Image Assessment for Obesity (self-perception of body); Mental Health Inventory; Block Food Frequency Questionnaire; Eating Behaviors and Chronic Conditions, Traditional Food Habits, and Food Preparation Technique questionnaires – and measures for Body Mass Index. Most rural, and premenopausal AAW were single and not living with a partner. Premenopausal women had significantly higher educational levels. Sixty percent of AAW had between 1 and 5 ORCHC. Most AAW used salt based seasonings, ate deep fried foods 1 to 3 times a week, and ate outside the home 1 to 3 times a month. Few AAW knew the correct daily serving for grains and dairy, and most consumed less than the recommended daily serving of fruits, vegetables and dairy. Morbidly obese AAW used more traditional food preparation techniques than obese and normal-weight AAW. Rural, and menopausal AAW had significantly higher morbid obesity levels, consumed larger portions of meats and vegetables, and reported more body image dissatisfaction than very rural AAW, and premenopausal AAW, respectively. Controlling for socioeconomic factors the relationships between perceptions of body images, psychological distress, and psychological wellbeing remained significant for numbers of ORCHC

Best Practices: Lessons Learned by a South Florida Non-Profit Community Based Organization while Designing and Implementing a Career Exploration Evidence Informed Framework in Urban Communities

All A’s was designed to support of the agency’s family strengthening initiatives in South Florida. All A’s uses evidence informed strategies poised to be an inclusive curriculum that teaches self-determination and adaptive behavior skills. The framework incorporates problem based learning and adult learning theory and follows the Universal Design for Learning. Since 2012, the agency has served over 8500 youth and 4,000 adults using the framework. The framework addresses educational underachievement and career readiness in at risk populations. It is used to enhance participants AWARENESS of setting SMART goals to achieve future goals and career aspirations. Participants are provided with ACCESS to resources and opportunities for creating and implementing an ACTION plan as they pursue and ACHIEVE their goals. All A’s promotes protective factors and expose youth to career pathways in Science, Technology, Engineering and Math (STEM) related fields. Youth participate in college tours, job site visits, job shadowing, high school visits, online college and career preparation assistance, service learning projects, STEM projects, and the Winning Futures© mentoring program. Adults are assisted with résumé development; learn job search strategies, interview techniques, job shadowing experiences, computer and financial literacy programs. Adults and youth are also given the opportunity to complete industry-recognized certifications in high demand industries (food service, general labor, and construction), and test preparation for the General Educational Development Test.

Resistance performances: (Re)constructing spaces of resistance and contention in the 2010-2011 University of Puerto Rico student movement

On the night of April 20, 2010, a group of students from the University of Puerto Rico (UPR), Río Piedras campus, met to organize an indefinite strike that quickly broadened into a defense of accessible public higher education of excellence as a fundamental right and not a privilege. Although the history of student activism in the UPR can be traced back to the early 1900s, the 2010-2011 strike will be remembered for the student activists’ use of new media technologies as resources that rapidly prompted and aided the numerous protests. ^ This activist research entailed a critical ethnography and a critical discourse analysis (CDA) of traditional and alternative media coverage and treatment during the 2010 -2011 UPR student strike. I examined the use of the 2010-2011 UPR student activists’ resistance performances in constructing local, corporeal, and virtual spaces of resistance and contention during their movement. In particular, I analyzed the different tactics and strategies of resistance or repertoire of collective actions that student activists used (e.g. new media technologies) to frame their collective identities via alternative news media’s (re)presentation of the strike, while juxtaposing the university administration’s counter-resistance performances in counter-framing the student activists’ collective identity via traditional news media representations of the strike. I illustrated how both traditional and alternative media (re)presentations of student activism developed, maintained, and/or modified students activists’ collective identities. ^ As such, the UPR student activism’s success should not be measured by the sum of demands granted, but by the sense of community achieved and the establishment of networks that continue to create resistance and change. These networks add to the debate surrounding Internet activism and its impact on student activism. Ultimately, the results of this study highlight the important role student movements have had in challenging different types of government policies and raising awareness of the importance of an accessible public higher education of excellence.^

A study of the effects of a service-learning experience on student success at an urban community college

The purpose of this study was to explore the effects of a service-learning experience on student success as measured by class attendance, course completion, final course grades, and end-of-term evaluation data.^ Though many outcomes of service-learning experiences have been studied, including ethical values, self-esteem, student personal development, and career preparation, relatively few studies have been conducted on the effects of such experiences on academic achievement, and the studies that have been done have primarily studied students at traditional, four-year, residential universities.^ The study consisted of 286 students enrolled in six paired courses taught by five instructors at a community college in the Fall term 1996. One section of each pair (the control group) was taught using traditional subject matter and course materials and the other section of each pair (the treatment group) participated in a 20-hour required service-learning activity in addition to the regular course curriculum. The courses in the study included American History, Sociology, College Preparatory English, and Introduction to English Composition.^ The results of this study indicate that, overall, students who participated in a class in which service-learning was a requirement, achieved higher final course grades and reported greater satisfaction with the course, the instructor, the reading assignments, and the grading system, and the treatment section of one course pair had fewer absences. In addition, the faculty members reported that, in the treatment sections, class discussions were more stimulating, the sections seemed more vital in terms of student involvement, the students seemed more challenged academically, more motivated to learn, and seemed to exert more effort in the course. ^

Performance of FRP-concrete bridges under blast loading

Catastrophic failure from intentional terrorist attacks on surface transportation infrastructure could he detrimental to the society. In order to minimize the vulnerabilities and to ensure a safe transportation system, the issue of security for transportation structures, primarily bridges, which are subjected to man-made hazards is investigated in this study. A procedure for identifying and prioritizing "critical bridges" using a screening and prioritization processes is established. For each of the "critical" bridges, a systematic risk-based assessment approach is proposed that takes into account the combination of threat occurrence likelihood, its consequences, and the socioeconomic importance of the bridge. A series of effective security countermeasures are compiled in the four categories of deterrence, detection, defense and mitigation to help reduce the vulnerability of critical bridges. The concepts of simplified equivalent I-shape cross section and virtual materials are proposed for integration into a nonlinear finite element model, which helps assess the performance of reinforced concrete structures with and without composite retrofit or hardening measures under blast loading. A series of parametric studies are conducted for single column and two-column pier frame systems as well as for an entire bridge. The parameters considered include column height, column type, concrete strength, longitudinal steel reinforcement ratio, thickness, fiber angle and tensile strength of the fiber reinforced polymer (FRP) tube, shape of the cross section, damping ratio and different bomb sizes. The study shows the benefits of hardening with composites against blast loading. The effect of steel reinforcement on blast resistance of the structure is more significant than the effect of concrete compressive strength. Moreover, multiple blasts do not necessarily lead to a more severe destruction than a single detonation at a strategically vulnerable location on the bridges.