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Title: Analysis of quality of service (QoS) in WiMAX networks.
Creator: Talwalkar, Rohit., College of Engineering and Computer Science, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In last few years there has been significant growth in the area of wireless communication. Quality of Service (QoS) has become an important consideration for supporting variety of applications that utilize the network resources. These applications include voice over IP, multimedia services, like, video streaming, video conferencing etc. IEEE 802.16/WiMAX is a new network which is designed with quality of service in mind. This thesis focuses on analysis of quality of service as implemented by...
Show moreIn last few years there has been significant growth in the area of wireless communication. Quality of Service (QoS) has become an important consideration for supporting variety of applications that utilize the network resources. These applications include voice over IP, multimedia services, like, video streaming, video conferencing etc. IEEE 802.16/WiMAX is a new network which is designed with quality of service in mind. This thesis focuses on analysis of quality of service as implemented by the WiMAX networks. First, it presents the details of the quality of service architecture in WiMAX network. In the analysis, a WiMAX module developed based on popular network simulator ns-2, is used. Various real life scenarios like voice call, video streaming are setup in the simulation environment. Parameters that indicate quality of service, such as, throughput, packet loss, average jitter and average delay, are analyzed for different types of service flows as defined in WiMAX. Results indicate that better quality of service is achieved by using service flows designed for specific applications.
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Date Issued: 2008
PURL: http://purl.flvc.org/fcla/flaent/EN00154040/68_2/98p0143h.pdf, http://purl.flvc.org/FAU/58012
Subject Headings: Wireless communication systems, Broadband communication systems, Wireless LANs, Design and construction, Computer networks, Management, Quality control
Format: Document (PDF)

Title: Accelerated curing of concrete with high volume pozzolans - resistivity, diffusivity and compressive strength.
Creator: Liu, Yanbo., College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description: This investigation presents results of the temperature effect on durability properties (resistivity and diffusivity) and compressive strength of concrete with pozzolans, and the effect of pozzolanic admixtures on microstructure and chemical compositions of concrete pore solution. ... Temperature dependence of electrical resistivity and chloride diffusivity was studied by dynamic temperature tests. Accelerated curing regimes involving curing concrete specimens in 35À C lime water with...
Show moreThis investigation presents results of the temperature effect on durability properties (resistivity and diffusivity) and compressive strength of concrete with pozzolans, and the effect of pozzolanic admixtures on microstructure and chemical compositions of concrete pore solution. ... Temperature dependence of electrical resistivity and chloride diffusivity was studied by dynamic temperature tests. Accelerated curing regimes involving curing concrete specimens in 35À C lime water with different durations were tested. Compressive strength test, resisivity measurement and rapid chloride migration (RCM) tests were performed. A leaching method was used to measure pH and conductivity of concrete pore solution. ... The accelerated curing regimes were found to increase the compressive strength and resistance to chloride ion penetration at short-term and long-term. With the developed correlation between resistivity and migration coefficients, it is possible to employ the resistivity measurement as an alternative or replacement of the RCM test to evaluate resistance of chloride ion penetration of concrete. Pozzolanic admixtures were found to decrease both pH and conductivity of concrete pore solution as the replacement ratio increased. Moreover, the migration coefficients were found to be greatly correlated to the microstructure properties of concrete, such as porosity, formation factor and tortuosity.
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Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3358603
Subject Headings: Pavements, Concrete, Additives, Quality control, Waste products as road materials, Reinforced concrete, Corrosion, Testing
Format: Document (PDF)

Title: Strength and durability of fly ash-based fiber-reinforced geopolymer concrete in a simulated marine environment.
Creator: Martinez Rivera, Francisco Javier, Sobhan, Khaled, College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description: This research is aimed at investigating the corrosion durability of polyolefin fiber-reinforced fly ash-based geopolymer structural concrete (hereafter referred to as GPC, in contradistinction to unreinforced geopolymer concrete referred to as simply geopolymer concrete), where cement is completely replaced by fly ash, that is activated by alkalis, sodium hydroxide and sodium silicate. The durability in a marine environment is tested through an electrochemical method for accelerated corrosion...
Show moreThis research is aimed at investigating the corrosion durability of polyolefin fiber-reinforced fly ash-based geopolymer structural concrete (hereafter referred to as GPC, in contradistinction to unreinforced geopolymer concrete referred to as simply geopolymer concrete), where cement is completely replaced by fly ash, that is activated by alkalis, sodium hydroxide and sodium silicate. The durability in a marine environment is tested through an electrochemical method for accelerated corrosion. The GPC achieved compressive strengths in excess of 6,000 psi. Fiber reinforced beams contained polyolefin fibers in the amounts of 0.1%, 0.3%, and 0.5% by volume. After being subjected to corrosion damage, the GPC beams were analyzed through a method of crack scoring, steel mass loss, and residual flexural strength testing. Fiber reinforced GPC beams showed greater resistance to corrosion damage with higher residual flexural strength. This makes GPC an attractive material for use in submerged marine structures.
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Date Issued: 2013
PURL: http://purl.flvc.org/fau/fd/FA0004037
Subject Headings: Concrete mixing -- Quality control, Green chemistry, Polymer composites, Reinforced concrete -- Corrosion -- Testing, Reinforced concrete construction
Format: Document (PDF)

Title: Prognostic COPD healthcare management system.
Creator: Jain, Piyush, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Hospital readmission rates are considered to be an important indicator of quality of care because they may be a consequence of actions of commission or omission made during the initial hospitalization of the patient, or as a consequence of poorly managed transition of the patient back into the community. The negative impact on patient quality of life and huge burden on healthcare system have made reducing hospital readmissions a central goal of healthcare delivery and payment reform efforts....
Show moreHospital readmission rates are considered to be an important indicator of quality of care because they may be a consequence of actions of commission or omission made during the initial hospitalization of the patient, or as a consequence of poorly managed transition of the patient back into the community. The negative impact on patient quality of life and huge burden on healthcare system have made reducing hospital readmissions a central goal of healthcare delivery and payment reform efforts. In this project, we will focus on COPD (Chronic Obstructive Pulmonary Disease) which is one of the leading causes of disability and mortality worldwide. This project will design and develop a prognostic COPD healthcare management system which is a sustainable clinical decision-support system to reduce the number of readmissions by identifying those patients who need preventive interventions to reduce the probability of being readmitted. Based on patient’s clinical records and discharge summary, our system would be able to determine the readmission risk profile of patients treated for COPD. Suitable interventions could then be initiated with the objective of providing quality and timely care that helps prevent avoidable readmission.
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Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00004125, http://purl.flvc.org/fau/fd/FA00004125
Subject Headings: Integrated delivery of health care, Lungs -- Diseases, Obstructive -- Treatment, Medical care -- Quality control
Format: Document (PDF)

Title: Classification of software quality using Bayesian belief networks.
Creator: Dong, Yuhong., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description: In today's competitive environment for software products, quality has become an increasingly important asset to software development organizations. Software quality models are tools for focusing efforts to find faults early in the development. Delaying corrections can lead to higher costs. In this research, the classification Bayesian Networks modelling technique was used to predict the software quality by classifying program modules either as fault-prone or not fault-prone. A general...
Show moreIn today's competitive environment for software products, quality has become an increasingly important asset to software development organizations. Software quality models are tools for focusing efforts to find faults early in the development. Delaying corrections can lead to higher costs. In this research, the classification Bayesian Networks modelling technique was used to predict the software quality by classifying program modules either as fault-prone or not fault-prone. A general classification rule was applied to yield classification Bayesian Belief Network models. Six classification Bayesian Belief Network models were developed based on quality metrics data records of two very large window application systems. The fit data set was used to build the model and the test data set was used to evaluate the model. The first two models used median based data cluster technique, the second two models used median as critical value to cluster metrics using Generalized Boolean Discriminant Function and the third two models used Kolniogorov-Smirnov test to select the critical value to cluster metrics using Generalized Boolean Discriminant Function; All six models used the product metrics (FAULT or CDCHURN) as predictors.
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Date Issued: 2002
PURL: http://purl.flvc.org/fcla/dt/12918
Subject Headings: Computer software--Quality control, Software measurement, Bayesian statistical decision theory
Format: Document (PDF)

Title: Classification of software quality using tree modeling with the S-Plus algorithm.
Creator: Deng, Jianyu., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description: In today's competitive environment for software products, quality has become an increasingly important asset to software development organizations. Software quality models are tools for focusing efforts to find faults early in the development. Delaying corrections can lead to higher costs. In this research, the classification tree modeling technique was used to predict the software quality by classifying program modules either as fault-prone or not fault-prone. The S-Plus regression tree...
Show moreIn today's competitive environment for software products, quality has become an increasingly important asset to software development organizations. Software quality models are tools for focusing efforts to find faults early in the development. Delaying corrections can lead to higher costs. In this research, the classification tree modeling technique was used to predict the software quality by classifying program modules either as fault-prone or not fault-prone. The S-Plus regression tree algorithm and a general classification rule were applied to yield classification tree models. Two classification tree models were developed based on four consecutive releases of a very large legacy telecommunications system. The first release was used as the training data set and the subsequent three releases were used as evaluation data sets. The first model used twenty-four product metrics and four execution metrics as candidate predictors. The second model added fourteen process metrics as candidate predictors.
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Date Issued: 1999
PURL: http://purl.flvc.org/fcla/dt/15707
Subject Headings: Computer software--Quality control, Software measurement, Computer software--Evaluation
Format: Document (PDF)

Title: Developing accurate software quality models using a faster, easier, and cheaper method.
Creator: Lim, Linda., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Managers of software development need to know which components of a system are fault-prone. If this can be determined early in the development cycle then resources can be more effectively allocated and significant costs can be reduced. Case-Based Reasoning (CBR) is a simple and efficient methodology for building software quality models that can provide early information to managers. Our research focuses on two case studies. The first study analyzes source files and classifies them as fault...
Show moreManagers of software development need to know which components of a system are fault-prone. If this can be determined early in the development cycle then resources can be more effectively allocated and significant costs can be reduced. Case-Based Reasoning (CBR) is a simple and efficient methodology for building software quality models that can provide early information to managers. Our research focuses on two case studies. The first study analyzes source files and classifies them as fault-prone or not fault-prone. It also predicts the number of faults in each file. The second study analyzes the fault removal process, and creates models that predict the outcome of software inspections.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/12746
Subject Headings: Computer software--Development, Computer software--Quality control, Software engineering
Format: Document (PDF)

Title: Partitioning filter approach to noise elimination: An empirical study in software quality classification.
Creator: Rebours, Pierre., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This thesis presents two new noise filtering techniques which improve the quality of training datasets by removing noisy data. The training dataset is first split into subsets, and base learners are induced on each of these splits. The predictions are combined in such a way that an instance is identified as noisy if it is misclassified by a certain number of base learners. The Multiple-Partitioning Filter combines several classifiers on each split. The Iterative-Partitioning Filter only uses...
Show moreThis thesis presents two new noise filtering techniques which improve the quality of training datasets by removing noisy data. The training dataset is first split into subsets, and base learners are induced on each of these splits. The predictions are combined in such a way that an instance is identified as noisy if it is misclassified by a certain number of base learners. The Multiple-Partitioning Filter combines several classifiers on each split. The Iterative-Partitioning Filter only uses one base learner, but goes through multiple iterations. The amount of noise removed is varied by tuning the filtering level or the number of iterations. Empirical studies on a high assurance software project compare the effectiveness of our noise removal approaches with two other filters, the Cross-Validation Filter and the Ensemble Filter. Our studies suggest that using several base classifiers as well as performing several iterations with a conservative scheme may improve the efficiency of the filter.
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Date Issued: 2004
PURL: http://purl.flvc.org/fcla/dt/13110
Subject Headings: Software measurement, Computer software--Quality control, Decision trees, Recursive partitioning
Format: Document (PDF)

Title: Prediction of software quality using classification tree modeling.
Creator: Naik, Archana B., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Reliability of software systems is one of the major concerns in today's world as computers have really become an integral part of our lives. Society has become so dependent on reliable software systems that failures can be dangerous in terms of worsening a company's business, human relationships or affecting human lives. Software quality models are tools for focusing efforts to find faults early in the development. In this experiment, we used classification tree modeling techniques to predict...
Show moreReliability of software systems is one of the major concerns in today's world as computers have really become an integral part of our lives. Society has become so dependent on reliable software systems that failures can be dangerous in terms of worsening a company's business, human relationships or affecting human lives. Software quality models are tools for focusing efforts to find faults early in the development. In this experiment, we used classification tree modeling techniques to predict the software quality by classifying program modules either as fault-prone or not fault-prone. We introduced the Classification And Regression Trees (scCART) algorithm as a tool to generate classification trees. We focused our experiments on very large telecommunications system to build quality models using set of product and process metrics as independent variables.
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Date Issued: 1998
PURL: http://purl.flvc.org/fcla/dt/15600
Subject Headings: Computer software--Quality control, Computer software--Evaluation, Software measurement
Format: Document (PDF)

Title: Multivariate modeling of software engineering measures.
Creator: Lanning, David Lee., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: One goal of software engineers is to produce software products. An additional goal, that the software production must lead to profit, releases the power of the software product market. This market demands high quality products and tight cycles in the delivery of new and enhanced products. These market conditions motivate the search for engineering methods that help software producers ship products quicker, at lower cost, and with fewer defects. The control of software defects is key to...
Show moreOne goal of software engineers is to produce software products. An additional goal, that the software production must lead to profit, releases the power of the software product market. This market demands high quality products and tight cycles in the delivery of new and enhanced products. These market conditions motivate the search for engineering methods that help software producers ship products quicker, at lower cost, and with fewer defects. The control of software defects is key to meeting these market conditions. Thus, many software engineering tasks are concerned with software defects. This study considers two sources of variation in the distribution of software defects: software complexity and enhancement activity. Multivariate techniques treat defect activity, software complexity, and enhancement activity as related multivariate concepts. Applied techniques include principal components analysis, canonical correlation analysis, discriminant analysis, and multiple regression analysis. The objective of this study is to improve our understanding of software complexity and software enhancement activity as sources of variation in defect activity, and to apply this understanding to produce predictive and discriminant models useful during testing and maintenance tasks. These models serve to support critical software engineering decisions.
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Date Issued: 1994
PURL: http://purl.flvc.org/fcla/dt/12383
Subject Headings: Software engineering, Computer software--Testing, Computer software--Quality control
Format: Document (PDF)

Title: Predicting decay in program modules of legacy software systems.
Creator: Joshi, Dhaval Kunvarabhai., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description: Legacy software systems may go through many releases. It is important to ensure that the reliability of a system improves with subsequent releases. Methods are needed to identify decaying software modules, i.e., modules for which quality decreases with each system release. Early identification of such modules during the software life cycle allows us to focus quality improvement efforts in a more productive manner, by reducing resources wasted for testing and improving the entire system. We...
Show moreLegacy software systems may go through many releases. It is important to ensure that the reliability of a system improves with subsequent releases. Methods are needed to identify decaying software modules, i.e., modules for which quality decreases with each system release. Early identification of such modules during the software life cycle allows us to focus quality improvement efforts in a more productive manner, by reducing resources wasted for testing and improving the entire system. We present a scheme to classify modules in three groups---Decayed, Improved, and Unchanged---based on a three-group software quality classification method. This scheme is applied to three different case studies, using a case-based reasoning three-group classification model. The model identifies decayed modules, and is validated over different releases. The main goal of this work is to focus on the evolution of program modules of a legacy software system to identify modules that are difficult to maintain and may need to be reengineered.
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Date Issued: 2002
PURL: http://purl.flvc.org/fcla/dt/12899
Subject Headings: Software reengineering, Computer software--Quality control, Software measurement, Software maintenance
Format: Document (PDF)

Title: An improved neural net-based approach for predicting software quality.
Creator: Guasti, Peter John., Florida Atlantic University, Khoshgoftaar, Taghi M., Pandya, Abhijit S.
Abstract/Description: Accurately predicting the quality of software is a major problem in any software development project. Software engineers develop models that provide early estimates of quality metrics which allow them to take action against emerging quality problems. Most often the predictive models are based upon multiple regression analysis which become unstable when certain data assumptions are not met. Since neural networks require no data assumptions, they are more appropriate for predicting software...
Show moreAccurately predicting the quality of software is a major problem in any software development project. Software engineers develop models that provide early estimates of quality metrics which allow them to take action against emerging quality problems. Most often the predictive models are based upon multiple regression analysis which become unstable when certain data assumptions are not met. Since neural networks require no data assumptions, they are more appropriate for predicting software quality. This study proposes an improved neural network architecture that significantly outperforms multiple regression and other neural network attempts at modeling software quality. This is demonstrated by applying this approach to several large commercial software systems. After developing neural network models, we develop regression models on the same data. We find that the neural network models surpass the regression models in terms of predictive quality on the data sets considered.
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Date Issued: 1995
PURL: http://purl.flvc.org/fcla/dt/15134
Subject Headings: Neural networks (Computer science), Computer software--Development, Computer software--Quality control, Software engineering
Format: Document (PDF)

Title: A comparative study of attribute selection techniques for CBR-based software quality classification models.
Creator: Nguyen, Laurent Quoc Viet., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: To achieve high reliability in software-based systems, software metrics-based quality classification models have been explored in the literature. However, the collection of software metrics may be a hard and long process, and some metrics may not be helpful or may be harmful to the classification models, deteriorating the models' accuracies. Hence, methodologies have been developed to select the most significant metrics in order to build accurate and efficient classification models. Case...
Show moreTo achieve high reliability in software-based systems, software metrics-based quality classification models have been explored in the literature. However, the collection of software metrics may be a hard and long process, and some metrics may not be helpful or may be harmful to the classification models, deteriorating the models' accuracies. Hence, methodologies have been developed to select the most significant metrics in order to build accurate and efficient classification models. Case-Based Reasoning is the classification technique used in this thesis. Since it does not provide any metric selection mechanisms, some metric selection techniques were studied. In the context of CBR, this thesis presents a comparative evaluation of metric selection methodologies, for raw and discretized data. Three attribute selection techniques have been studied: Kolmogorov-Smirnov Two-Sample Test, Kruskal-Wallis Test, and Information Gain. These techniques resulted in classification models that are useful for software quality improvement.
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Date Issued: 2002
PURL: http://purl.flvc.org/fcla/dt/12944
Subject Headings: Case-based reasoning, Software engineering, Computer software--Quality control
Format: Document (PDF)

Title: Fuzzy logic techniques for software reliability engineering.
Creator: Xu, Zhiwei., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Modern people are becoming more and more dependent on computers in their daily lives. Most industries, from automobile, avionics, oil, and telecommunications to banking, stocks, and pharmaceuticals, require computers to function. As the tasks required become more complex, the complexity of computer software and hardware has increased dramatically. As a consequence, the possibility of failure increases. As the requirements for and dependence on computers increases, the possibility of crises...
Show moreModern people are becoming more and more dependent on computers in their daily lives. Most industries, from automobile, avionics, oil, and telecommunications to banking, stocks, and pharmaceuticals, require computers to function. As the tasks required become more complex, the complexity of computer software and hardware has increased dramatically. As a consequence, the possibility of failure increases. As the requirements for and dependence on computers increases, the possibility of crises caused by computer failures also increases. High reliability is an important attribute for almost any software system. Consequently, software developers are seeking ways to forecast and improve quality before release. Since many quality factors cannot be measured until after the software becomes operational, software quality models are developed to predict quality factors based on measurements collected earlier in the life cycle. Due to incomplete information in the early life cycle of software development, software quality models with fuzzy characteristics usually perform better because fuzzy concepts deal with phenomenon that is vague in nature. This study focuses on the usage of fuzzy logic in software reliability engineering. Discussing will include the fuzzy expert systems and the application of fuzzy expert systems in early risk assessment; introducing the interval prediction using fuzzy regression modeling; demonstrating fuzzy rule extraction for fuzzy classification and its usage in software quality models; demonstrating the fuzzy identification, including extraction of both rules and membership functions from fuzzy data and applying the technique to software project cost estimations. The following methodologies were considered: nonparametric discriminant analysis, Z-test and paired t-test, neural networks, fuzzy linear regression, fuzzy nonlinear regression, fuzzy classification with maximum matched method, fuzzy identification with fuzzy clustering, and fuzzy projection. Commercial software systems and the COCOMO database are used throughout this dissertation to demonstrate the usefulness of concepts and to validate new ideas.
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Date Issued: 2001
PURL: http://purl.flvc.org/fcla/dt/11948
Subject Headings: Software engineering, Fuzzy logic, Computer software--Quality control, Fuzzy systems
Format: Document (PDF)

Title: Knowledge Discovery Through Drive Test Data Visualization.
Creator: Saxena, Shalini, Pandya, Abhijit S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: With the increasing number of cellular phone service subscribers, the telecommunications service providers have placed immense emphasis on improving audio quality and ensure fewer dropped calls. Handoff behavior of all handsets is an important factor in quality of service of a mobile phone service. This thesis focuses on the analysis of large volumes of diagnostic data collected from mobile phones in the real world and the identification of aberrant behavior of a mobile handset under test by...
Show moreWith the increasing number of cellular phone service subscribers, the telecommunications service providers have placed immense emphasis on improving audio quality and ensure fewer dropped calls. Handoff behavior of all handsets is an important factor in quality of service of a mobile phone service. This thesis focuses on the analysis of large volumes of diagnostic data collected from mobile phones in the real world and the identification of aberrant behavior of a mobile handset under test by means of drive test data visualization. Our target was to identify poor mobility decisions that are made by the handsets in calls. Premature, delayed or exceedingly sensitive decisions are considered poor mobility decisions. The goal was to compare a set of behaviors from a baseline unit (one accepted to generally operate well). We were able to identify a particular call that was exhibiting a different path (talking to a different cell than expected or taking longer to move to a new cell). We designed a chi-square statistical test to evaluate the performance of specific mobile handset models. We also developed a mobility tool that evaluated the handset's performance by means of mapping the handoffs on the Google Maps. The mapping of the handoffs by means of the Google Maps were very powerful in identifying the above mentioned mobility patterns.
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Date Issued: 2007
PURL: http://purl.flvc.org/fau/fd/FA00012548
Subject Headings: Mobile communication systems--Quality control, Wireless communication systems--Technological innovations, Cellular telephones--Design
Format: Document (PDF)

Title: Meteorological Conditions Affecting the Dispersion of Landfill Odor Complaints.
Creator: Vidovic, Mateja, Meeroff, Daniel E., Florida Atlantic University, College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description: One of the factors recognized as affecting the dispersion of landfill odors off-site are complex meteorological conditions. A major issue is lack of consistent means to identify the odors and their intensity. The aim of this research was to investigate the influence of meteorological parameters (temperature, humidity, pressure, wind direction, wind speed, precipitation accumulation and weather conditions) on the frequency of odor complaints from nearby neighborhoods. Methods involved...
Show moreOne of the factors recognized as affecting the dispersion of landfill odors off-site are complex meteorological conditions. A major issue is lack of consistent means to identify the odors and their intensity. The aim of this research was to investigate the influence of meteorological parameters (temperature, humidity, pressure, wind direction, wind speed, precipitation accumulation and weather conditions) on the frequency of odor complaints from nearby neighborhoods. Methods involved collection of ten years of data on odor complaints and weather conditions to determine if there were commonalities. Sophisticated statistical analyses employed did not reveal any relationships between odor complaints and weather alone. Need for substantial improvement of detailed information is recognized. To help identify the factors that influence odor complaints- a revised odor complaint form, along with operational adjustments, were recommended. An “Odor Threat Assessment Level” is proposed to assist landfill site personnel in managing daily operations, based on weather conditions.
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Date Issued: 2017
PURL: http://purl.flvc.org/fau/fd/FA00004947, http://purl.flvc.org/fau/fd/FA00004947
Subject Headings: Landfill gases--Measurement., Odor control., Air quality management., Refuse and refuse disposal.
Format: Document (PDF)

Title: Cost of misclassification in software quality models.
Creator: Guan, Xin., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description: Reliability has become a very important and competitive factor for software products. Using software quality models based on software measurements provides a systematic and scientific way to detect software faults early and to improve software reliability. This thesis considers several classification techniques including Generalized Classification Rule, MetaCost algorithm, Cost-Boosting algorithm and AdaCost algorithm. We also introduce the weighted logistic regression algorithm, and a new...
Show moreReliability has become a very important and competitive factor for software products. Using software quality models based on software measurements provides a systematic and scientific way to detect software faults early and to improve software reliability. This thesis considers several classification techniques including Generalized Classification Rule, MetaCost algorithm, Cost-Boosting algorithm and AdaCost algorithm. We also introduce the weighted logistic regression algorithm, and a new method to evaluate the performance of classification models---ROC Analysis. We focus our experiments on a very large legacy telecommunications system (LLTS) to build software quality models with principal components analysis. Two other data sets, CCCS and LTS are also used in our experiments.
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Date Issued: 2000
PURL: http://purl.flvc.org/fcla/dt/15762
Subject Headings: Computer software--Quality control, Software measurement, Computer software--Testing
Format: Document (PDF)

Title: A metrics-based software quality modeling tool.
Creator: Rajeevalochanam, Jayanth Munikote., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In today's world, high reliability has become an essential component of almost every software system. However, since the reliability-enhancement activities entail enormous costs, software quality models, based on the metrics collected early in the development life cycle, serve as handy tools for cost-effectively guiding such activities to the software modules that are likely to be faulty. Case-Based Reasoning (CBR) is an attractive technique for software quality modeling. Software Measurement...
Show moreIn today's world, high reliability has become an essential component of almost every software system. However, since the reliability-enhancement activities entail enormous costs, software quality models, based on the metrics collected early in the development life cycle, serve as handy tools for cost-effectively guiding such activities to the software modules that are likely to be faulty. Case-Based Reasoning (CBR) is an attractive technique for software quality modeling. Software Measurement Analysis and Reliability Toolkit (SMART) is a CBR tool customized for metrics-based software quality modeling. Developed for the NASA IV&V Facility, SMART supports three types of software quality models: quantitative quality prediction, classification, and module-order models. It also supports a goal-oriented selection of classification models. An empirical case study of a military command, control, and communication system demonstrates the accuracy and usefulness of SMART, and also serves as a user-guide for the tool.
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Date Issued: 2002
PURL: http://purl.flvc.org/fcla/dt/12967
Subject Headings: Software measurement, Computer software--Quality control, Case-based reasoning
Format: Document (PDF)

Title: Software reliability engineering with genetic programming.
Creator: Liu, Yi., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Software reliability engineering plays a vital role in managing and controlling software quality. As an important method of software reliability engineering, software quality estimation modeling is useful in defining a cost-effective strategy to achieve a reliable software system. By predicting the faults in a software system, the software quality models can identify high-risk modules, and thus, these high-risk modules can be targeted for reliability enhancements. Strictly speaking, software...
Show moreSoftware reliability engineering plays a vital role in managing and controlling software quality. As an important method of software reliability engineering, software quality estimation modeling is useful in defining a cost-effective strategy to achieve a reliable software system. By predicting the faults in a software system, the software quality models can identify high-risk modules, and thus, these high-risk modules can be targeted for reliability enhancements. Strictly speaking, software quality modeling not only aims at lowering the misclassification rate, but also takes into account the costs of different misclassifications and the available resources of a project. As a new search-based algorithm, Genetic Programming (GP) can build a model without assuming the size, shape, or structure of a model. It can flexibly tailor the fitness functions to the objectives chosen by the customers. Moreover, it can optimize several objectives simultaneously in the modeling process, and thus, a set of multi-objective optimization solutions can be obtained. This research focuses on building software quality estimation models using GP. Several GP-based models of predicting the class membership of each software module and ranking the modules by a quality factor were proposed. The first model of categorizing the modules into fault-prone or not fault-prone was proposed by considering the distinguished features of the software quality classification task and GP. The second model provided quality-based ranking information for fault-prone modules. A decision tree-based software classification model was also proposed by considering accuracy and simplicity simultaneously. This new technique provides a new multi-objective optimization algorithm to build decision trees for real-world engineering problems, in which several trade-off objectives usually have to be taken into account at the same time. The fourth model was built to find multi-objective optimization solutions by considering both the expected cost of misclassification and available resources. Also, a new goal-oriented technique of building module-order models was proposed by directly optimizing several goals chosen by project analysts. The issues of GP , bloating and overfitting, were also addressed in our research. Data were collected from three industrial projects, and applied to validate the performance of the models. Results indicate that our proposed methods can achieve useful performance results. Moreover, some proposed methods can simultaneously optimize several different objectives of a software project management team.
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Date Issued: 2003
PURL: http://purl.flvc.org/fau/fd/FADT12047
Subject Headings: Computer software--Quality control, Genetic programming (Computer science), Software engineering
Format: Document (PDF)

Title: Software quality prediction using case-based reasoning.
Creator: Berkovich, Yevgeniy., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description: The ability to efficiently prevent faults in large software systems is a very important concern of software project managers. Successful testing allows us to build quality software systems. Unfortunately, it is not always possible to effectively test a system due to time, resources, or other constraints. A critical bug may cause catastrophic consequences, such as loss of life or very expensive equipment. We can facilitate testing by finding where faults are more likely to be hidden. Case...
Show moreThe ability to efficiently prevent faults in large software systems is a very important concern of software project managers. Successful testing allows us to build quality software systems. Unfortunately, it is not always possible to effectively test a system due to time, resources, or other constraints. A critical bug may cause catastrophic consequences, such as loss of life or very expensive equipment. We can facilitate testing by finding where faults are more likely to be hidden. Case-Based Reasoning (CBR) is one of many methodologies that make this process faster and cheaper by discovering faults early in the software life cycle. This is one of the methodologies used to predict software quality of the system by discovering fault-prone modules. We employ the SMART tool to facilitate CBR , using product and process metrics as independent variables. The study found that CBR is a robust tool capable of carrying out software quality prediction on its own with acceptable results. We also show that CBR's weaknesses do not hinder its effectiveness in finding misclassified modules.
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Date Issued: 2000
PURL: http://purl.flvc.org/fcla/dt/12671
Subject Headings: Computer software--Quality control, Computer software--Evaluation, Software measurement
Format: Document (PDF)

FAU Theses and Dissertations (81)	+ -
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Quality control (14)	+ -
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Case-based reasoning (3)	+ -
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Reinforced concrete (3)	+ -
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Computer network architecture (2)	+ -
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Electronic Thesis or Dissertation (81)	+ -
article (1)	+ -
technical report (1)	+ -

Florida Atlantic University (69)	+ -
College of Engineering and Computer Science (52)	+ -
Department of Computer and Electrical Engineering and Computer Science (43)	+ -
Khoshgoftaar, Taghi M. (43)	+ -
Department of Ocean and Mechanical Engineering (6)	+ -

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