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Title: Rough Set-Based Software Quality Models and Quality of Data.
Creator: Bullard, Lofton A., Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In this dissertation we address two significant issues of concern. These are software quality modeling and data quality assessment. Software quality can be measured by software reliability. Reliability is often measured in terms of the time between system failures. A failure is caused by a fault which is a defect in the executable software product. The time between system failures depends both on the presence and the usage pattern of the software. Finding faulty components in the development...
Show moreIn this dissertation we address two significant issues of concern. These are software quality modeling and data quality assessment. Software quality can be measured by software reliability. Reliability is often measured in terms of the time between system failures. A failure is caused by a fault which is a defect in the executable software product. The time between system failures depends both on the presence and the usage pattern of the software. Finding faulty components in the development cycle of a software system can lead to a more reliable final system and will reduce development and maintenance costs. The issue of software quality is investigated by proposing a new approach, rule-based classification model (RBCM) that uses rough set theory to generate decision rules to predict software quality. The new model minimizes over-fitting by balancing the Type I and Type II niisclassiflcation error rates. We also propose a model selection technique for rule-based models called rulebased model selection (RBMS). The proposed rule-based model selection technique utilizes the complete and partial matching rule sets of candidate RBCMs to determine the model with the least amount of over-fitting. In the experiments that were performed, the RBCMs were effective at identifying faulty software modules, and the RBMS technique was able to identify RBCMs that minimized over-fitting. Good data quality is a critical component for building effective software quality models. We address the significance of the quality of data on the classification performance of learners by conducting a comprehensive comparative study. Several trends were observed in the experiments. Class and attribute had the greatest impact on the performance of learners when it occurred simultaneously in the data. Class noise had a significant impact on the performance of learners, while attribute noise had no impact when it occurred in less than 40% of the most significant independent attributes. Random Forest (RF100), a group of 100 decision trees, was the most, accurate and robust learner in all the experiments with noisy data.
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Date Issued: 2008
PURL: http://purl.flvc.org/fau/fd/FA00012567
Subject Headings: Computer software--Quality control, Computer software--Reliability, Software engineering, Computer arithmetic
Format: Document (PDF)

Title: Tree-based classification models for analyzing a very large software system.
Creator: Bullard, Lofton A., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description: Software systems that control military radar systems must be highly reliable. A fault can compromise safety and security, and even cause death of military personnel. In this experiment we identify fault-prone software modules in a subsystem of a military radar system called the Joint Surveillance Target Attack Radar System, JSTARS. An earlier version was used in Operation Desert Storm to monitor ground movement. Product metrics were collected for different iterations of an operational...
Show moreSoftware systems that control military radar systems must be highly reliable. A fault can compromise safety and security, and even cause death of military personnel. In this experiment we identify fault-prone software modules in a subsystem of a military radar system called the Joint Surveillance Target Attack Radar System, JSTARS. An earlier version was used in Operation Desert Storm to monitor ground movement. Product metrics were collected for different iterations of an operational prototype of the subsystem over a period of approximately three years. We used these metrics to train a decision tree model and to fit a discriminant model to classify each module as fault-prone or not fault-prone. The algorithm used to generate the decision tree model was TREEDISC, developed by the SAS Institute. The decision tree model is compared to the discriminant model.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15315
Subject Headings: Computer software--Quality control, Computer software--Reliability, Software engineering
Format: Document (PDF)

Title: Identifying descriptions of quality nursing care shared by nurse and patient in the acute care hospital environment.
Creator: Grimley, Karen A., Tappen, Ruth M., Florida Atlantic University, Christine E. Lynn College of Nursing
Abstract/Description: Nursing care is considered a primary predictor of patient assessment of the overall hospital experience. Yet, quality nursing care remains difficult to define. Limited research about nurse or patient perspectives on what constitutes quality nursing care in hospital settings prevents the identification of a shared description or insight into their possible interrelationship. Research about nurse and patient descriptions is needed to establish behaviors, attributes, and activities associated...
Show moreNursing care is considered a primary predictor of patient assessment of the overall hospital experience. Yet, quality nursing care remains difficult to define. Limited research about nurse or patient perspectives on what constitutes quality nursing care in hospital settings prevents the identification of a shared description or insight into their possible interrelationship. Research about nurse and patient descriptions is needed to establish behaviors, attributes, and activities associated with quality nursing care to improve the health and well-being of hospitalized patients.
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Date Issued: 2015
PURL: http://purl.flvc.org/fau/fd/FA00004375
Subject Headings: Nursing--Philosophy, Nurse and patient, Medical care--Quality control, Intensive care nursing--Quality control, Outcome assessment--Medical care, Total quality management, Evidence-based nursing.
Format: Document (PDF)

Title: The Role of Cues in Buyers' Evaluations of Service Innovations.
Creator: Ramesan, Jayendra, Florida Atlantic University, Georgoff, David M.
Abstract/Description: This dissertation integrates knowledge from consumer behavior, diffusion research, strategy and MIS to investigate the effects of information cues such as price, brand equity, and technology on buyers' service evaluations and behavioral intentions. Specifically, the effects of these information cues on buyers' perceptions of service quality, value and purchase intentions are examined. In addition, this study examines the role of two intervening variables, namely, sacrifice (monetary costs)...
Show moreThis dissertation integrates knowledge from consumer behavior, diffusion research, strategy and MIS to investigate the effects of information cues such as price, brand equity, and technology on buyers' service evaluations and behavioral intentions. Specifically, the effects of these information cues on buyers' perceptions of service quality, value and purchase intentions are examined. In addition, this study examines the role of two intervening variables, namely, sacrifice (monetary costs) and ease of use (non-monetary costs) in buyers' service evaluations. Two interactive services, a home banking service (Citibank & Ameritech) and a home shopping service (Time Warner) were described in a concept test format to subjects in a 4 x 2 x 2 between-subjects factorial design experiment. The sample for the home banking service (281) was composed of undergraduate students drawn from the university while the sample for the home shopping service (409), was composed of individuals living in the South Florida area. The experimental treatments, manipulation checks, dependent and intervening variables were measured using multiple-item seven point Likert-type scales. The data was analyzed using econometric modeling techniques. In both experiments, service quality perceptions were found to be significantly influenced by technology and brand equity perceptions. Brand equity was the main determinant of service quality in both experiments. Service value perceptions were driven by direct effects from service quality, sacrifice and ease of use and indirectly driven by technology and price perceptions. The role of brand equity in value perceptions is ambiguous. Sacrifice was related positively to price perceptions in both studies. Purchase intentions were explained only by value perceptions in both studies. The results suggest that service quality and service value are very different. The value function is more complex than service quality. Service organizations that attempt to create customer value by maximizing service quality ratings at the lowest price need to emphasize other value based determinants such as technology and ease of use. The model suggests a crossfunctional approach should be employed for service design and development in order to maximize service quality and customer value. In addition, this study recommends a substantive pre-launch service concept development and delivery effort by service organizations before introducing new services.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/12452
Subject Headings: Human Information Processing--Research, Consumer Satisfaction--Evaluation, Marketing--Management, Quality of Products--Evaluation, Technological innovations, Customer services--Quality control
Format: Document (PDF)

Title: Compliance Issues In Cloud Computing Systems.
Creator: Yimam, Dereje, Fernandez, Eduardo B., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Appealing features of cloud services such as elasticity, scalability, universal access, low entry cost, and flexible billing motivate consumers to migrate their core businesses into the cloud. However, there are challenges about security, privacy, and compliance. Building compliant systems is difficult because of the complex nature of regulations and cloud systems. In addition, the lack of complete, precise, vendor neutral, and platform independent software architectures makes compliance even...
Show moreAppealing features of cloud services such as elasticity, scalability, universal access, low entry cost, and flexible billing motivate consumers to migrate their core businesses into the cloud. However, there are challenges about security, privacy, and compliance. Building compliant systems is difficult because of the complex nature of regulations and cloud systems. In addition, the lack of complete, precise, vendor neutral, and platform independent software architectures makes compliance even harder. We have attempted to make regulations clearer and more precise with patterns and reference architectures (RAs). We have analyzed regulation policies, identified overlaps, and abstracted them as patterns to build compliant RAs. RAs should be complete, precise, abstract, vendor neutral, platform independent, and with no implementation details; however, their levels of detail and abstraction are still debatable and there is no commonly accepted definition about what an RA should contain. Existing approaches to build RAs lack structured templates and systematic procedures. In addition, most approaches do not take full advantage of patterns and best practices that promote architectural quality. We have developed a five-step approach by analyzing features from available approaches but refined and combined them in a new way. We consider an RA as a big compound pattern that can improve the quality of the concrete architectures derived from it and from which we can derive more specialized RAs for cloud systems. We have built an RA for HIPAA, a compliance RA (CRA), and a specialized compliance and security RA (CSRA) for cloud systems. These RAs take advantage of patterns and best practices that promote software quality. We evaluated the architecture by creating profiles. The proposed approach can be used to build RAs from scratch or to build new RAs by abstracting real RAs for a given context. We have also described an RA itself as a compound pattern by using a modified POSA template. Finally, we have built a concrete deployment and availability architecture derived from CSRA that can be used as a foundation to build compliance systems in the cloud.
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Date Issued: 2015
PURL: http://purl.flvc.org/fau/fd/FA00004559, http://purl.flvc.org/fau/fd/FA00004559
Subject Headings: Biometric identification, Client/server computing -- Security measures, Cloud computing -- Security measures, Computational intelligence, Computer software -- Quality control, Electronic information resources -- Access control
Format: Document (PDF)

Title: A Clinical Decision Support System for the Identification of Potential Hospital Readmission Patients.
Creator: Baechle, Christopher, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Recent federal legislation has incentivized hospitals to focus on quality of patient care. A primary metric of care quality is patient readmissions. Many methods exist to statistically identify patients most likely to require hospital readmission. Correct identification of high-risk patients allows hospitals to intelligently utilize limited resources in mitigating hospital readmissions. However, these methods have seen little practical adoption in the clinical setting. This research attempts...
Show moreRecent federal legislation has incentivized hospitals to focus on quality of patient care. A primary metric of care quality is patient readmissions. Many methods exist to statistically identify patients most likely to require hospital readmission. Correct identification of high-risk patients allows hospitals to intelligently utilize limited resources in mitigating hospital readmissions. However, these methods have seen little practical adoption in the clinical setting. This research attempts to identify the many open research questions that have impeded widespread adoption of predictive hospital readmission systems. Current systems often rely on structured data extracted from health records systems. This data can be expensive and time consuming to extract. Unstructured clinical notes are agnostic to the underlying records system and would decouple the predictive analytics system from the underlying records system. However, additional concerns in clinical natural language processing must be addressed before such a system can be implemented. Current systems often perform poorly using standard statistical measures. Misclassification cost of patient readmissions has yet to be addressed and there currently exists a gap between current readmission system evaluation metrics and those most appropriate in the clinical setting. Additionally, data availability for localized model creation has yet to be addressed by the research community. Large research hospitals may have sufficient data to build models, but many others do not. Simply combining data from many hospitals often results in a model which performs worse than using data from a single hospital. Current systems often produce a binary readmission classification. However, patients are often readmitted for differing reasons than index admission. There exists little research into predicting primary cause of readmission. Furthermore, co-occurring evidence discovery of clinical terms with primary diagnosis has seen only simplistic methods applied. This research addresses these concerns to increase adoption of predictive hospital readmission systems.
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Date Issued: 2017
PURL: http://purl.flvc.org/fau/fd/FA00004880, http://purl.flvc.org/fau/fd/FA00004880
Subject Headings: Health services administration--Management., Medical care--Quality control--Statistical methods., Medical care--Quality control--Data processing., Medical care--Decision making., Evidence-based medicine., Outcome assessment (Medical care)
Format: Document (PDF)

Title: Experimental evaluation of the durability of fly ash-based geopolymer concrete in the marine environment.
Creator: Edouard, Jean-Baptiste., College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description: The construction industry is increasingly turning to the use of environmentally friendly materials in order to meet the sustainable aspect required by modern infrastructures. Consequently, for the last two decades, the expansion of this concept, and the increasing global warming have raised concerns on the extensive use of Portland cement due to the high amount of carbon dioxide gas associated with its production. The development of geopolymer concretes offers promising signs for a change in...
Show moreThe construction industry is increasingly turning to the use of environmentally friendly materials in order to meet the sustainable aspect required by modern infrastructures. Consequently, for the last two decades, the expansion of this concept, and the increasing global warming have raised concerns on the extensive use of Portland cement due to the high amount of carbon dioxide gas associated with its production. The development of geopolymer concretes offers promising signs for a change in the way of producing concrete. However, to seriously consider geopolymer binders as an alternative to ordinary Portland cement, the durability of this new material should be evaluated in any comparative analysis. The main purpose of this study was to evaluate the durability characteristics of low calcium fly ash-based geopolymer concretes subjected to the marine environment, compared to ordinary Portland cement concrete with similar exposure. To achieve this goal, 8 molar geopolymer, 14 molar geopolymer and ordinary Portland cement concrete mixes were prepared and tested for exposure in seawater. Compressive strengths in the range of 2900 to 8700 psi (20-60 MPa) were obtained. The corrosion resistance performance of steel-reinforced concrete beams, made of these mixes, was also studied, using an accelerated electrochemical method, with submergence in salt water. The test results indicated that the geopolymer concrete showed excellent resistance to chloride attack, with longer time to corrosion cracking, compared to ordinary Portland cement concrete.
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Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3170960
Subject Headings: Reinforced concrete, Corrosion, Testing, Reinforced concrete construction, Concrete, Mixing, Quality control, Environmental chemistry, Industrial applications, Polymer composites
Format: Document (PDF)

Title: The impact of satisfaction with care and empowerment on glycemic control among older African American adults with diabetes.
Creator: Johnson, Bridgette M., Christine E. Lynn College of Nursing
Abstract/Description: atisfaction with diabetes care, perceived feelings of empowerment to participate in self-care management, and glycemic control in a sample of older African American men and women with diabetes. A descriptive correlational quantitative design was used. The participants in this study were 73 men and women of African descent who were at least 50 years, English speaking, and diagnosed with diabetes for at least one year. The participants were asked to complete three survey instruments: the...
Show moreatisfaction with diabetes care, perceived feelings of empowerment to participate in self-care management, and glycemic control in a sample of older African American men and women with diabetes. A descriptive correlational quantitative design was used. The participants in this study were 73 men and women of African descent who were at least 50 years, English speaking, and diagnosed with diabetes for at least one year. The participants were asked to complete three survey instruments: the Patient Satisfaction Questionnaire-18 (PSQ-18), which measured how satisfied the participants were with their medical care; the Diabetes Empowerment Scale-Short Form (DES-SF), which measured attitudes towards diabetes and self-management of diabetes; and a demographic form, which collected data on the demographics of each participant. The most recent hemoglobin A1c (HbA1c) of each participant was obtained from the medical records. The correlations between HbA1c, DES, and the PSQ-18 subscales were exam ined. The study data indicated all correlations were statistically significant and negative with one exception. There was no correlation between HbA1c and time spent, a satisfaction subscale. Approximately half the participants were high school graduates, married, and reported being born in the Caribbean. Most had primary care physicians, but less than half reported attending a diabetes education program. The average BMI was 33.0. The findings of this study indicated older African adults who reported higher satisfaction with the care provided by their health care provider reported feeling more empowered to participate in diabetes self-care and reported lower HbA1c levels, suggesting better glycemic control (R2 = .39; P=<.001)., The implications of this study are that feeling empowered to participate in diabetes self-care management may result in improved glycemic control. Positive diabetes outcomes have been linked in the literature with persons feeling empowered to participate in diabetes self-care. The significance of the findings from this study is that given the relationship between empowerment and glycemic control, nurses should support the empowerment model of diabetes teaching. Diabetes education should provide written materials that are culturally sensitive for African American elders.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342114
Subject Headings: Outcome assessment (Medical care), Nursing, Quality control, Medical economics, Patient satisfaction, Evaluation, African Americans, Health and hygiene, Sociological aspects
Format: Document (PDF)

Title: A web-based automated classification system for nursing language based on nursing theory.
Creator: Dass, Subhomoy D., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Health care systems consist of various individuals and organizations that aim to meet the health care needs of people and provide a complete and responsive health care solution. One of the important aspects of a health care delivery system is nursing. The use of technology is a vital aspect for delivering an optimum and complete nursing care to individuals; and also for improving the quality and delivery mechanism of nursing care. The model proposed in this thesis for Nursing Knowledge...
Show moreHealth care systems consist of various individuals and organizations that aim to meet the health care needs of people and provide a complete and responsive health care solution. One of the important aspects of a health care delivery system is nursing. The use of technology is a vital aspect for delivering an optimum and complete nursing care to individuals; and also for improving the quality and delivery mechanism of nursing care. The model proposed in this thesis for Nursing Knowledge Management System is a novel knowledge-based decision support system for nurses to capture and manage nursing practice, and further, to monitor nursing care quality, as well as to test aspects of an electronic health record for recording and reporting nursing practice. As a part of a collaborative research of the Christine E. Lynn College of Nursing and the Department of Computer Science, a prototype toolset was developed to capture and manage nursing practice in order to improve the quality of care. This thesis focuses on implementing a web based SOA solution for Automated Classification of Nursing Care Categories, based on the knowledge gained from the prototype for nursing care practice.
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Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3332184
Subject Headings: Nursing, Quality control, Outcome asssessment (Medical care), Nursing assessment, Digital techiques, Nursing, Computer-assisted instruction, Nursing informatics
Format: Document (PDF)

Title: Prognosis and health monitoring communications quality of service.
Creator: Tavtilov, Timur, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This thesis research was funded by the Southeast National Marine Renewable Energy Center (SNMREC) at Florida Atlantic University. Its objective is the development of Quality of Service (QoS) mechanisms for the wireless communications architecture used by the Prognosis and Health Monitoring (PHM) subsystem. There are numerous technical challenges that the PHM Communications Subsystem tries to solve. Due to ocean platform mobility from waves, currents, and other environmental factors, signal...
Show moreThis thesis research was funded by the Southeast National Marine Renewable Energy Center (SNMREC) at Florida Atlantic University. Its objective is the development of Quality of Service (QoS) mechanisms for the wireless communications architecture used by the Prognosis and Health Monitoring (PHM) subsystem. There are numerous technical challenges that the PHM Communications Subsystem tries to solve. Due to ocean platform mobility from waves, currents, and other environmental factors, signal quality can vary significantly. As a result, the wireless link between the electric generator platform and shore systems will have variable quality in terms of data rate, delay, and availability. In addition, the data traffic that flows from generator sensors and PHM applications to the shore systems consists of numerous types of messages that have different QoS demands (e.g. delay) and priority that depends on the message type, user ID, sensor location, and application-dependent parameters. The PHM Communications subsystem must handle effectively high priority messages, such as alarms, alerts, and remote control commands from shore systems. It also performs QoS in the application layer, so it can read the contents of every message to prioritize them. In order to perform QoS in the application layer the PHM subsystem relies on Java Servlet multithreaded technology and different queuing techniques to control message transmission order. Furthermore, it compresses all traffic that comes from the ocean-based electric generator/turbine platform to reduce the load on the wireless link. The PHM Communications subsystem consists of three components: the wireless link, the Link Manager, and the Web Services Network Proxy. We present experimental results for the Web Services Network Proxy and demonstrate the effectiveness of XML data compression and semantic-based message scheduling over a link with variable capacity.
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Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3334098
Subject Headings: Computer network architecture, Service-oriented architecture (Computer science), Wireless communication services, Technological innovations, Wireless communication services, Quality control
Format: Document (PDF)

Title: CBR-based software quality models and quality of data.
Creator: Xiao, Yudong., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The performance accuracy of software quality estimation models is influenced by several factors, including the following two important factors: performance of the prediction algorithm and the quality of data. This dissertation addresses these two factors, and consists of two components: (1) a proposed genetic algorithm (GA) based optimization of software quality models for accuracy enhancement, and (2) a proposed partitioning- and rule-based filter (PRBF) for noise detection toward...
Show moreThe performance accuracy of software quality estimation models is influenced by several factors, including the following two important factors: performance of the prediction algorithm and the quality of data. This dissertation addresses these two factors, and consists of two components: (1) a proposed genetic algorithm (GA) based optimization of software quality models for accuracy enhancement, and (2) a proposed partitioning- and rule-based filter (PRBF) for noise detection toward improvement of data quality. We construct a generalized framework of our embedded GA-optimizer, and instantiate the GA-optimizer for three optimization problems in software quality engineering: parameter optimization for case-based reasoning (CBR) models; module rank optimization for module-order modeling (MOM); and structural optimization for our multi-strategy classification modeling approach, denoted RB2CBL. Empirical case studies using software measurement data from real-world software systems were performed for the optimization problems. The GA-optimization approaches improved software quality prediction accuracy, highlighting the practical benefits of using GA for solving optimization problems in software engineering. The proposed noise detection approach, PRBF, was empirically evaluated using data categorized into two classes. Empirical studies on artificially corrupted datasets and datasets with known (natural) noise demonstrated that PRBF can effectively detect both artificial and natural noise. The proposed filter is a stable and robust technique, and always provided optimal or near-optimal noise detection results. In addition, it is applicable on datasets with nominal and numerical attributes, as well as those with missing values. The PRBF technique supports two methods of noise detection: class noise detection and cost-sensitive noise detection. The former is an easy-to-use method and does not need parameter settings, while the latter is suited for applications where each class has a specific misclassification cost. PRBF can also be used iteratively to investigate the two general types of data noise: attribute and class noise.
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Date Issued: 2005
PURL: http://purl.flvc.org/fcla/dt/12141
Subject Headings: Computer software--Quality control, Genetic programming (Computer science), Software engineering, Case-based reasoning, Combinatorial optimization, Computer network architecture
Format: Document (PDF)

Title: Improved models of software quality.
Creator: Szabo, Robert Michael., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Though software development has been evolving for over 50 years, the development of computer software systems has largely remained an art. Through the application of measurable and repeatable processes, efforts have been made to slowly transform the software development art into a rigorous engineering discipline. The potential gains are tremendous. Computer software pervades modern society in many forms. For example, the automobile, radio, television, telephone, refrigerator, and still-camera...
Show moreThough software development has been evolving for over 50 years, the development of computer software systems has largely remained an art. Through the application of measurable and repeatable processes, efforts have been made to slowly transform the software development art into a rigorous engineering discipline. The potential gains are tremendous. Computer software pervades modern society in many forms. For example, the automobile, radio, television, telephone, refrigerator, and still-camera have all been transformed by the introduction of computer based controls. The quality of these everyday products is in part determined by the quality of the computer software running inside them. Therefore, the timely delivery of low-cost and high-quality software to enable these mass market products becomes very important to the long term success of the companies building them. It is not surprising that managing the number of faults in computer software to competitive levels is a prime focus of the software engineering activity. In support of this activity, many models of software quality have been developed to help control the software development process and ensure that our goals of cost and quality are met on time. In this study, we focus on the software quality modeling activity. We improve existing static and dynamic methodologies and demonstrate new ones in a coordinated attempt to provide engineering methods applicable to the development of computer software. We will show how the power of separate predictive and classification models of software quality may be combined into one model; introduce a three group fault classification model in the object-oriented paradigm; demonstrate a dynamic modeling methodology of the testing process and show how software product measures and software process measures may be incorporated as input to such a model; demonstrate a relationship between software product measures and the testability of software. The following methodologies were considered: principal components analysis, multiple regression analysis, Poisson regression analysis, discriminant analysis, time series analysis, and neural networks. Commercial grade software systems are used throughout this dissertation to demonstrate concepts and validate new ideas. As a result, we hope to incrementally advance the state of the software engineering "art".
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/12409
Subject Headings: Software engineering--Standards, Software engineering--Management, Computer software--Development, Computer software--Quality control
Format: Document (PDF)

Title: Prediction of crude oil product quality parameters using neural networks.
Creator: Bawazeer, Khalid Ahmed., Florida Atlantic University, Zilouchian, Ali
Abstract/Description: Inferential analysis using neural networks technology is being proposed for the Ras Tanura Refinery crude fractionation section. Plant data for a three month operation period is analyzed in order to construct a neural network model with backpropagation training algorithm. The proposed neural network model can predict various properties associated with crude oil products. The simulation results for modeling Naphtha 95% cut point and Naphtha Reid vapor pressure properties are analyzed. A fuzzy...
Show moreInferential analysis using neural networks technology is being proposed for the Ras Tanura Refinery crude fractionation section. Plant data for a three month operation period is analyzed in order to construct a neural network model with backpropagation training algorithm. The proposed neural network model can predict various properties associated with crude oil products. The simulation results for modeling Naphtha 95% cut point and Naphtha Reid vapor pressure properties are analyzed. A fuzzy neural network model is also proposed that takes into account the fuzziness in both process variables and the corresponding product quality parameter. The training algorithm is derived based on the backpropagation technique. The results of the proposed study can ultimately enhance the on-line prediction of crude oil product quality parameters for crude fractionation processes in the Ras Tanura Oil Refinery.
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Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15302
Subject Headings: Petroleum products--Analysis, Petroleum products--Testing, Petroleum industry and trade--Quality control, Neural networks (Computer science)
Format: Document (PDF)

Title: An analysis of the impact of non-audit services on financial reporting quality: A test of two competing theories of auditor independence.
Creator: Dickins, Denise., Florida Atlantic University, Skantz, Terrance R.
Abstract/Description: Auditor independence has been a long-standing issue for regulators resulting in numerous studies on the subject on how to enhance it and numerous rules that attempt to ensure it (e.g. Cohen Report 1978; ASR 250 1978; SEC Rule 2-01 2000). One of regulators' most recent attempts to shore up auditor independence is evident in the provisions of the Sarbanes-Oxley Act of 2002 (SOX). As a test of two competing theories of auditor independence, and to determine whether SOX mandates have successfully...
Show moreAuditor independence has been a long-standing issue for regulators resulting in numerous studies on the subject on how to enhance it and numerous rules that attempt to ensure it (e.g. Cohen Report 1978; ASR 250 1978; SEC Rule 2-01 2000). One of regulators' most recent attempts to shore up auditor independence is evident in the provisions of the Sarbanes-Oxley Act of 2002 (SOX). As a test of two competing theories of auditor independence, and to determine whether SOX mandates have successfully enhanced financial reporting quality, I examine post-SOX changes in non-audit fees (as a proxy for changes in quasi-rents) and the extent of changes in two measures of financial reporting quality. Results suggest that SOX mandates have been effective, and that the proposition of DeAngelo (1981b) that non-audit services may impair auditor independence may more-closely describe the relationship between changes in quasi-rents and changes in financial reporting quality than does the theory of Lee and Gu (1998). Further, supplemental analyses suggest that, as proposed by the theories, the amount of low-balling is positively related to the amount of quasi-rents.
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Date Issued: 2006
PURL: http://purl.flvc.org/fcla/dt/12195
Subject Headings: Auditors--Evaluation, Accounting--Standards--United States, Auditing--Standards--United States, Auditing--Quality control, Disclosure in accounting
Format: Document (PDF)

Title: An empirical study of combining techniques in software quality classification.
Creator: Eroglu, Cemal., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description: In the literature, there has been limited research that systematically investigates the possibility of exercising a hybrid approach by simply learning from the output of numerous base-level learners. We analyze a hybrid learning approach upon the systems that had previously been worked with twenty-four different classifiers. Instead of relying on only one classifier's judgment, it is expected that taking into account the opinions of several learners is a wise decision. Moreover, by using...
Show moreIn the literature, there has been limited research that systematically investigates the possibility of exercising a hybrid approach by simply learning from the output of numerous base-level learners. We analyze a hybrid learning approach upon the systems that had previously been worked with twenty-four different classifiers. Instead of relying on only one classifier's judgment, it is expected that taking into account the opinions of several learners is a wise decision. Moreover, by using clustering techniques some base-level classifiers were eliminated from the hybrid learner input. We had three different experiments each with a different number of base-level classifiers. We empirically show that the hybrid learning approach generally yields better performance than the best selected base-level learners and majority voting under some conditions.
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Date Issued: 2004
PURL: http://purl.flvc.org/fcla/dt/13162
Subject Headings: Computer software--Testing, Computer software--Quality control, Computational learning theory, Machine learning, Digital computer simulation
Format: Document (PDF)

Title: An examination of the southern association of colleges and schools commission on colleges’ quality enhancement plans at two institutions through the lens of quality improvement.
Creator: Rodriguez, Barbara June, Floyd, Deborah L., Maslin-Ostrowski, Patricia, Florida Atlantic University, College of Education, Department of Educational Leadership and Research Methodology
Abstract/Description: The purpose of this case study was to explore the quality enhancement plan (QEP) process and its influence on student learning of critical thinking and the institutional environment from the perspective of key stakeholders at two community colleges accredited by the Southern Association of Colleges and Schools Commission on Colleges (the Commission). Key stakeholders were defined as faculty, staff, and administrators who had direct and continuous involvement with the development and/or...
Show moreThe purpose of this case study was to explore the quality enhancement plan (QEP) process and its influence on student learning of critical thinking and the institutional environment from the perspective of key stakeholders at two community colleges accredited by the Southern Association of Colleges and Schools Commission on Colleges (the Commission). Key stakeholders were defined as faculty, staff, and administrators who had direct and continuous involvement with the development and/or implementation of the QEP. This was accomplished through document reviews and analysis of interviews. The study was guided by intertwined quality assurance systems accountability, accreditation, and assessment, and six of Deming’s (1986) total quality management principles. These principles are: (1) customer, (2) training and development, (3) teamwork, (4) measurement, (5) improvement, and (6) leadership (Bosner, 1992; Deming, 1986; Marchese, 1991; Sallis, 2002).
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Date Issued: 2015
PURL: http://purl.flvc.org/fau/fd/FA00004404, http://purl.flvc.org/fau/fd/FA00004404
Subject Headings: Educational evaluation -- Case studies, Educational tests and measurements -- Case studies, School management and organization -- Quality control -- Case studies, Total quality management in education -- Case studies, Universities and colleges -- Accreditation -- Case studies
Format: Document (PDF)

Title: A Systematic Review and Quantitative Meta-Analysis of the Accuracy of Visual Inspection for Cervical Cancer Screening: Does Provider Type or Training Matter?.
Creator: Driscoll, Susan D., Tappen, Ruth M., Florida Atlantic University, Christine E. Lynn College of Nursing
Abstract/Description: Background: A global cervical cancer health disparity persists despite the demonstrated success of primary and secondary preventive strategies, such as cervical visual inspection (VI). Cervical cancer is the leading cause of cancer incidence and death for women in many low resource areas. The greatest risk is for those who are unable or unwilling to access screening. Barriers include healthcare personnel shortages, cost, transportation, and mistrust of healthcare providers and systems. Using...
Show moreBackground: A global cervical cancer health disparity persists despite the demonstrated success of primary and secondary preventive strategies, such as cervical visual inspection (VI). Cervical cancer is the leading cause of cancer incidence and death for women in many low resource areas. The greatest risk is for those who are unable or unwilling to access screening. Barriers include healthcare personnel shortages, cost, transportation, and mistrust of healthcare providers and systems. Using community health workers (CHWs) may overcome these barriers, increase facilitators, and improve participation in screening for women in remote areas with limited access to clinical resources. Aim: To determine whether the accuracy of VI performed by CHWs was comparable to VI by physicians or nurses and to consider the affect components of provider training had on VI accuracy. Methods: A systematic review and quantitative meta-analysis of published literature reporting on VI accuracy, provider type, and training was conducted. Strict inclusion/exclusion criteria, study quality, and publication bias assessments improved rigor and bivariate linear mixed modeling (BLMM) was used to determine the affect of predictors on accuracy. Unconditional and conditional BLMMs, controlling for VI technique, provider type, community, clinical setting, HIV status, and gynecological symptoms were considered. Results: Provider type was a significant predictor of sensitivity (p=.048) in the unconditional VI model. VI performed by CHWs was 15% more sensitive than physicians (p=.014). Provider type was not a significant predictor of accuracy in any other models. Didactic and mentored hours predicted sensitivity in both BLMMs. Quality assurance and use of a training manual predicted specificity in unconditional BLMMs, but was not significant in conditional models. Number of training days, with ≤5 being optimal, predicted sensitivity in both BLMMs and specificity in the unconditional model. Conclusion: Study results suggest that community based cervical cancer screening with VI conducted by CHWs can be as, if not more, accurate than VI performed by licensed providers. Locally based screening programs could increase access to screening for women in remote areas. Collaborative partnerships in “pragmatic solidarity” between healthcare systems, CHWs, and the community could promote participation in screening resulting in decreased cervical cancer incidence and mortality.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004755
Subject Headings: Women--Health and hygiene., Cervix uteri--Cancer--Diagnosis., Cervix uteri--Cancer--Prevention., Medical screening., Medical care--Quality control., Community health services.
Format: Document (PDF)

Title: Can Priming a Firm’s Organizational Identity Overcome the Influences of National Culture on Auditor Judgment?.
Creator: Killey, Michael, Higgs, Julia, Florida Atlantic University, College of Business, School of Accounting
Abstract/Description: A significant challenge faced by large auditing firms is offering consistent quality across the global network. Unfortunately, variation in judgments and decision-making, resulting from cultural differences, can undermine the provision of a uniform level of audit quality for these international firms. Previous research has determined that national culture influences an auditors’ professional judgments and decisions. Relying on Social Identity Theory, I explore whether inducing one’s...
Show moreA significant challenge faced by large auditing firms is offering consistent quality across the global network. Unfortunately, variation in judgments and decision-making, resulting from cultural differences, can undermine the provision of a uniform level of audit quality for these international firms. Previous research has determined that national culture influences an auditors’ professional judgments and decisions. Relying on Social Identity Theory, I explore whether inducing one’s organizational identification can both enhance auditor judgment and mitigate any deleterious impact that culture may have on the provision of a uniform level of audit quality. I also examine current cultural variations in auditor judgment in order to ensure that the results of earlier studies still typify the international auditing environment. National culture is assessed using two dimensions (individualism/collectivism, power distance) included in Hofstede’s 1980 cultural values framework. Participants from the United States are used to represent an individualistic/low power distance culture while individuals from India are used to represent a collectivistic/high power distance culture. Firms need mechanisms to elicit desired behaviors that may not be consistent with cultural tendencies in order to provide a uniform level of audit quality. Contrary to expectations, no significant differences are identified between the judgments of auditors from India and The United States. The results, however, do provide evidence that enhancing one’s organizational identification can impact certain professional judgments during the audit process. An association between national culture and auditor attitudes pertaining to client trust is also found. The implications of these findings for the professional auditing environment and future academic research are discussed.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004736, http://purl.flvc.org/fau/fd/FA00004736
Subject Headings: Corporate governance., Corporations--Auditing., Auditing--Quality control., Identity (Psychology), Accounting--Moral and ethical aspects., Accounting--Professional ethics., Social responsibility of business.
Format: Document (PDF)

Title: Personal health record system and integration techniques with various electronic medical record systems.
Creator: Ved, Vishesh., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In order to improve the quality of care, there is urgent need to involve patients in their own healthcare. So to make patient centered health care system Personal Health Records are proposed as viable solution. This research discusses the importance of a Patient Centric Health Record system. Such systems can empower patients to participate in improving health care quality. It would also provide an economically viable solution to the need for better healthcare without escalating costs by...
Show moreIn order to improve the quality of care, there is urgent need to involve patients in their own healthcare. So to make patient centered health care system Personal Health Records are proposed as viable solution. This research discusses the importance of a Patient Centric Health Record system. Such systems can empower patients to participate in improving health care quality. It would also provide an economically viable solution to the need for better healthcare without escalating costs by avoiding duplication. The proposed system is Web-based; therefore it has high accessibility and availability. The cloud computing based architecture is used which will allow consumers to address the challenge of sharing medical data. PHR would provide a complete and accurate summary of the health and medical history of an individual by gathering data from many sources. This would make information accessible online to anyone who has the necessary electronic credentials to view the information.
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Date Issued: 2010
PURL: http://purl.flvc.org/FAU/1930491
Subject Headings: Medical records, Data processing, Management, Medical informatics, Information storage and retrieval systems, Medical care, Medical care, Quality control, Personal information management
Format: Document (PDF)

Title: Text Mining and Topic Modeling for Social and Medical Decision Support.
Creator: Hurtado, Jose Luis, Zhu, Xingquan, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Effective decision support plays vital roles in people's daily life, as well as for professional practitioners such as health care providers. Without correct information and timely derived knowledge, a decision is often suboptimal and may result in signi cant nancial loss or compromises of the performance. In this dissertation, we study text mining and topic modeling and propose to use text mining methods, in combination with topic models, to discover knowledge from texts popularly available...
Show moreEffective decision support plays vital roles in people's daily life, as well as for professional practitioners such as health care providers. Without correct information and timely derived knowledge, a decision is often suboptimal and may result in signi cant nancial loss or compromises of the performance. In this dissertation, we study text mining and topic modeling and propose to use text mining methods, in combination with topic models, to discover knowledge from texts popularly available from a wide variety of sources, such as research publications, news, medical diagnose notes, and further employ discovered knowledge to assist social and medical decision support. Examples of such decisions include hospital patient readmission prediction, which is a national initiative for health care cost reduction, academic research topics discovery and trend modeling, and social preference modeling for friend recommendation in social networks etc. To carry out text mining, our research, in Chapter 3, first emphasizes on single document analyzing to investigate textual stylometric features for user pro ling and recognition. Our research confirms that by using properly designed features, it is possible to identify the authors who wrote the article, using a number of sample articles written by the author as the training data. This study serves as the base to assert that text mining is a powerful tool for capturing knowledge in texts for better decision making. In the Chapter 4, we advance our research from single documents to documents with interdependency relationships, and propose to model and predict citation relationship between documents. Given a collection of documents with known linkage relationships, our research will discover e ective features to train prediction models, and predict the likelihood of two documents involving a citation relationships. This study will help accurately model social network linkage relationships, and can be used to assist e ective decision making for friend recommendation in social networking, and reference recommendation in scienti c writing etc. In the Chapter 5, we advance a topic discovery and trend prediction principle to discover meaningful topics from a set of data collection, and further model the evolution trend of the topic. By proposing techniques to discover topics from text, and using temporal correlation between trend for prediction, our techniques can be used to summarize a large collection of documents as meaningful topics, and further forecast the popularity of the topic in a near future. This study can help design systems to discover popular topics in social media, and further assist resource planning and scheduling based on the discovered topics and the their evolution trend. In the Chapter 6, we employ both text mining and topic modeling to the medical domain for effective decision making. The goal is to discover knowledge from medical notes to predict the risk of a patient being re-admitted in a near future. Our research emphasizes on the challenge that re-admitted patients are only a small portion of the patient population, although they bring signficant financial loss. As a result, the datasets are highly imbalanced which often result in poor accuracy for decision making. Our research will propose to use latent topic modeling to carryout localized sampling, and combine models trained from multiple copies of sampled data for accurate prediction. This study can be directly used to assist hospital re-admission assessment for early warning and decision support. The text mining and topic modeling techniques investigated in the dissertation can be applied to many other domains, involving texts and social relationships, towards pattern and knowledge based e ective decision making.
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Date Issued: 2016
PURL: http://purl.flvc.org/fau/fd/FA00004782, http://purl.flvc.org/fau/fd/FA00004782
Subject Headings: Social sciences--Research--Methodology., Data mining., Machine learning., Database searching., Discourse analysis--Data processing., Communication--Network analysis., Medical care--Quality control.
Format: Document (PDF)

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