View All Items

Title: APIS: A SOFTWARE AND HARDWARE TOOLKIT FOR FEDERATED POWER MANAGEMENT IN ENERGY HARVESTING APPLICATIONS.
Creator: Prey, Adam, Hallstrom, Jason O., Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description: Embedded systems and Internet of Things (IoT) devices have been limited in application by constraints posed by batteries. Batteries add size, weight, and upkeep costs, while also limiting the lifetime of devices that are preferred to be small, lightweight, and long-lasting. We present Apis, a software and hardware toolkit for federated power management in energy harvesting applications. By replacing batteries with rapid charging storage capacitors, circuitry to control federated energy...
Show moreEmbedded systems and Internet of Things (IoT) devices have been limited in application by constraints posed by batteries. Batteries add size, weight, and upkeep costs, while also limiting the lifetime of devices that are preferred to be small, lightweight, and long-lasting. We present Apis, a software and hardware toolkit for federated power management in energy harvesting applications. By replacing batteries with rapid charging storage capacitors, circuitry to control federated energy storage, and software support to make this architecture useful to developers, embedded devices can potentially run inde nitely with limited maintenance. We present the Apis hardware design for controlling federated energy storage, supporting software for controlling this hardware, and the results of experiments performed to validate the Apis model. The system is named after the taxonomy genus for the honey bee, a creature dedicated to the harvesting and federated storage of energy resources.
Show less
Date Issued: 2019
PURL: http://purl.flvc.org/fau/fd/FA00013405
Subject Headings: Internet of things, Energy harvesting, Embedded systems (Computer systems), Telecommunication--Power supply, Application program interfaces (Computer software)
Format: Document (PDF)

Title: Application level intrusion detection using a sequence learning algorithm.
Creator: Dong, Yuhong., Florida Atlantic University, Hsu, Sam, Rajput, Saeed, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: An un-supervised learning algorithm on application level intrusion detection, named Graph Sequence Learning Algorithm (GSLA), is proposed in this dissertation. Experiments prove its effectiveness. Similar to most intrusion detection algorithms, in GSLA, the normal profile needs to be learned first. The normal profile is built using a session learning method, which is combined with the one-way Analysis of Variance method (ANOVA) to determine the value of an anomaly threshold. In the proposed...
Show moreAn un-supervised learning algorithm on application level intrusion detection, named Graph Sequence Learning Algorithm (GSLA), is proposed in this dissertation. Experiments prove its effectiveness. Similar to most intrusion detection algorithms, in GSLA, the normal profile needs to be learned first. The normal profile is built using a session learning method, which is combined with the one-way Analysis of Variance method (ANOVA) to determine the value of an anomaly threshold. In the proposed approach, a hash table is used to store a sparse data matrix in triple data format that is collected from a web transition log instead of an n-by-n dimension matrix. Furthermore, in GSLA, the sequence learning matrix can be dynamically changed according to a different volume of data sets. Therefore, this approach is more efficient, easy to manipulate, and saves memory space. To validate the effectiveness of the algorithm, extensive simulations have been conducted by applying the GSLA algorithm to the homework submission system at our computer science and engineering department. The performance of GSLA is evaluated and compared with traditional Markov Model (MM) and K-means algorithms. Specifically, three major experiments have been done: (1) A small data set is collected as a sample data, and is applied to GSLA, MM, and K-means algorithms to illustrate the operation of the proposed algorithm and demonstrate the detection of abnormal behaviors. (2) The Random Walk-Through sampling method is used to generate a larger sample data set, and the resultant anomaly score is classified into several clusters in order to visualize and demonstrate the normal and abnormal behaviors with K-means and GSLA algorithms. (3) Multiple professors' data sets are collected and used to build the normal profiles, and the ANOVA method is used to test the significant difference among professors' normal profiles. The GSLA algorithm can be made as a module and plugged into the IDS as an anomaly detection system.
Show less
Date Issued: 2006
PURL: http://purl.flvc.org/fcla/dt/12220
Subject Headings: Data mining, Parallel processing (Electronic computers), Computer algorithms, Computer security, Pattern recognition systems
Format: Document (PDF)

Title: Application of artificial neural networks to deduce robust forecast performance in technoeconomic contexts.
Creator: Dabbas, Mohammad A., Neelakanta, Perambur S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The focus of this research is concerned with performing forecasting in technoeconomic contexts using a set of certain novel artificial neural networks (ANNs). Relevant efforts in general, entail the task of quantitatively estimating the details about the likelihood of future events (or unknown outcomes/effects) based on past and current information on the observed events (or known causes). Commensurate with the scope and objectives of the research, the specific topics addressed are as follows...
Show moreThe focus of this research is concerned with performing forecasting in technoeconomic contexts using a set of certain novel artificial neural networks (ANNs). Relevant efforts in general, entail the task of quantitatively estimating the details about the likelihood of future events (or unknown outcomes/effects) based on past and current information on the observed events (or known causes). Commensurate with the scope and objectives of the research, the specific topics addressed are as follows: A review on various methods adopted in technoeconomic forecasting and identified are econometric projections that can be used for forecasting via artificial neural network (ANN)-based simulations Developing and testing a compatible version of ANN designed to support a dynamic sigmoidal (squashing) function that morphs to the stochastical trends of the ANN input. As such, the network architecture gets pruned for reduced complexity across the span of iterative training schedule leading to the realization of a constructive artificial neural-network (CANN). Formulating a training schedule on an ANN with sparsely-sampled data via sparsity removal with cardinality enhancement procedure (through Nyquist sampling) and invoking statistical bootstrapping technique of resampling applied on the cardinality-improved subset so as to obtain an enhanced number of pseudoreplicates required as an adequate ensemble for robust training of the test ANN: The training and prediction exercises on the test ANN corresponds to optimally elucidating output predictions in the context of the technoeconomics framework of the power generation considered Prescribing a cone-of-error to alleviate over- or under-predictions toward prudently interpreting the results obtained; and, squeezing the cone-of-error to get a final cone-of-forecast rendering the forecast estimation/inference to be more precise Designing an ANN-based fuzzy inference engine (FIE) to ascertain the ex ante forecast details based on sparse sets of ex post data gathered in technoeconomic contexts - Involved thereof a novel method of .fusing fuzzy considerations and data sparsity.Lastly, summarizing the results with essential conclusions and identifying possible research items for future efforts identified as open-questions.
Show less
Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00004097, http://purl.flvc.org/fau/fd/FA00004097
Subject Headings: Artificial intelligence, Fuzzy systems, Long waves (Economics), Multisensor data fusion, Neural networks (Computer science) -- Mathematical models
Format: Document (PDF)

Title: APPLICATION OF BLOCKCHAIN NETWORK FOR THE USE OF INFORMATION SHARING.
Creator: Zamir, Linir, Liu, Feng-Hao, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The Blockchain concept was originally developed to provide security in the Bitcoin cryptocurrency network, where trust is achieved through the provision of an agreed-upon and immutable record of transactions between parties. The use of a Blockchain as a secure, publicly distributed ledger is applicable to fields beyond finance, and is an emerging area of research across many other fields in the industry. This thesis considers the feasibility of using a Blockchain to facilitate secured...
Show moreThe Blockchain concept was originally developed to provide security in the Bitcoin cryptocurrency network, where trust is achieved through the provision of an agreed-upon and immutable record of transactions between parties. The use of a Blockchain as a secure, publicly distributed ledger is applicable to fields beyond finance, and is an emerging area of research across many other fields in the industry. This thesis considers the feasibility of using a Blockchain to facilitate secured information sharing between parties, where a lack of trust and absence of central control are common characteristics. Implementation of a Blockchain Information Sharing system will be designed on an existing Blockchain network with as a communicative party members sharing secured information. The benefits and risks associated with using a public Blockchain for information sharing will also be discussed.
Show less
Date Issued: 2019
PURL: http://purl.flvc.org/fau/fd/FA00013351
Subject Headings: Blockchains (Databases), Blockchains (Databases)--Industrial applications, Data encryption (Computer science), Personal data protection, Bitcoin
Format: Document (PDF)

Title: APPLICATION OF LINE SPECTRUM PAIRS TO TONE DETECTION (SINEWAVE, FREQUENCIES, SINUSOIDAL, PREDICTIVE, AUTOCORRELATION).
Creator: WODKE, KENNETH E., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This thesis deals with the application of Line Spectrum Pairs to tone detection. Linear Predictive Coding (LPC) is described as a background to deriving the Line Spectrum Pairs. Two sources of LPC prediction coefficients are used to calcul?te Line Spectrum Pairs. One source is the polynomial roots of an LPC inverse filter; various locations of up to 3 pairs of complex conjugate roots are used to provide filter coefficients. The radii of the conjugate roots are varied to see the effect on the...
Show moreThis thesis deals with the application of Line Spectrum Pairs to tone detection. Linear Predictive Coding (LPC) is described as a background to deriving the Line Spectrum Pairs. Two sources of LPC prediction coefficients are used to calcul?te Line Spectrum Pairs. One source is the polynomial roots of an LPC inverse filter; various locations of up to 3 pairs of complex conjugate roots are used to provide filter coefficients. The radii of the conjugate roots are varied to see the effect on the calculated Line Spectrum Pairs. A second source of the filter coefficients is single and multiple sinusoidal tones that are LPC analyzed by the autocorrelation method to generate filter prediction coefficients. The frequencies and amplitudes of the summed sinusoids, and the length of the LPC analysis window are varied to determine the ability to detect the sinusoids by calculating the related Line Spectrum Pairs.
Show less
Date Issued: 1986
PURL: http://purl.flvc.org/fcla/dt/14328
Subject Headings: Speech processing systems
Format: Document (PDF)

Title: Application of MoM: Scattering calculations using condition number.
Creator: Zhuang, Zhijun., Florida Atlantic University, Bagby, Jonathan S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Computational accuracy is widely recognized as a critical issue in applied electromagnetics. Increasing computational power is being applied to solve more complex electromagnetic systems with an emphasis on computational accuracy. The work of this thesis is focused on the implementation of Method of Moments (MoM) to integral equation formulations. The goal of this effort is to use what is known as condition number, and, a heuristic rule-of-thumb is applied to investigate the computational...
Show moreComputational accuracy is widely recognized as a critical issue in applied electromagnetics. Increasing computational power is being applied to solve more complex electromagnetic systems with an emphasis on computational accuracy. The work of this thesis is focused on the implementation of Method of Moments (MoM) to integral equation formulations. The goal of this effort is to use what is known as condition number, and, a heuristic rule-of-thumb is applied to investigate the computational accuracy of MoM in numerical electromagnetics. Other possible applications of condition number of the MoM matrix are also indicated.
Show less
Date Issued: 1999
PURL: http://purl.flvc.org/fcla/dt/15719
Subject Headings: Electromagnetism, Moments method (Statistics), Electromagnetic theory, Integral equations--Numerical solutions
Format: Document (PDF)

Title: Application of stochastical mixture theory in the design of electromagnetic composite materials.
Creator: Katragadda, Subramaniam., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This Thesis is concerned with the application of stochastical mixture considerations in the analytical modeling of certain classes of electromagnetic composites. It refers to the elucidation of the electromagnetic properties of such composite materials when used in engineering applications. The analytical studies refer to the extension of the existing stochastical mixture permittivity formulations to characterize magnetic mixture materials as well as chiralic mixture media. In both cases the...
Show moreThis Thesis is concerned with the application of stochastical mixture considerations in the analytical modeling of certain classes of electromagnetic composites. It refers to the elucidation of the electromagnetic properties of such composite materials when used in engineering applications. The analytical studies refer to the extension of the existing stochastical mixture permittivity formulations to characterize magnetic mixture materials as well as chiralic mixture media. In both cases the mixture medium is presumed to consist of a host (receptacle) and dispersed particulates (inclusions). The effects of particulate shape in both chiralic and achiralic systems are also considered. Further, the concept of particulate polarization in deciding the permittivity and/or permeability characteristics of orderly-textured mixture media is addressed so as to determine the electromagnetic properties of such orderly-textured media. Application potentials of the present studies in the design of electromagnetic composites are indicated and the scope for the future research is portrayed.
Show less
Date Issued: 1992
PURL: http://purl.flvc.org/fcla/dt/14807
Subject Headings: Composite materials, Stochastic processes
Format: Document (PDF)

Title: Application of wavelets to image and video coding.
Creator: Zolghadr, Esfandiar, Florida Atlantic University, Furht, Borko, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In this thesis we applied wavelet transforms to image and video coding. First, a survey of various wavelets and their features is presented, including continuous, discrete, and orthogonal wavelets. Theories and concepts underlying one and two-dimensional wavelet transforms are introduced and compared to Fourier transform and sub-band coding. The core of the thesis is the implementation of two-dimensional and three-dimensional codec architectures and their application to coding images and...
Show moreIn this thesis we applied wavelet transforms to image and video coding. First, a survey of various wavelets and their features is presented, including continuous, discrete, and orthogonal wavelets. Theories and concepts underlying one and two-dimensional wavelet transforms are introduced and compared to Fourier transform and sub-band coding. The core of the thesis is the implementation of two-dimensional and three-dimensional codec architectures and their application to coding images and videos, respectively. We studied performance of the wavelet codec by comparing it to DCT and JPEG coding techniques. We applied these techniques for compression of a variety of test images and videos. We also analyzed the adaptability and scalability of 2D and 3D codec. Experimental results, presented in the thesis, illustrate the superior performance of wavelets compared to other coding techniques.
Show less
Date Issued: 2003
PURL: http://purl.flvc.org/fcla/dt/13050
Subject Headings: Wavelets (Mathematics), Image compression, JPEG (Image coding standard)
Format: Document (PDF)

Title: Applications of pulse width modulation to LEDs, fuel cells and battery technology.
Creator: Watt, Wayne W., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: It has become a case of great desire and, in some instances, a requirement to have systems in engineering be energy efficient, in addition to being effectively powerful. It is rare that there is a single technique that has the range to make this possible in a wide collection of areas in the field. The work done in this thesis exhibits how Pulse Width Modulation (PWM) bridges LEDs, plug in vehicles, fuel cells and batteries, all seemingly different sub categories of electrical engineering. It...
Show moreIt has become a case of great desire and, in some instances, a requirement to have systems in engineering be energy efficient, in addition to being effectively powerful. It is rare that there is a single technique that has the range to make this possible in a wide collection of areas in the field. The work done in this thesis exhibits how Pulse Width Modulation (PWM) bridges LEDs, plug in vehicles, fuel cells and batteries, all seemingly different sub categories of electrical engineering. It stems from an undergraduate directed independent study supervised by Dr. Zilouchian that encircled LEDs and electric vehicles and how they contribute to a smart electric grid. This thesis covers the design and development of a prototype board that test how PWM saves energy, prolongs lifespan and provides a host of customizable features in manufactured LED lights that are used in the marine industry. Additionally, the concept of charging batteries that provide power to electric vehicles was explored. It is stressed that consumers who are interested in electric vehicles are concerned about refueling and recharge times. It is natural that a competing product, such as the electric vehicle in a world dominated by internal combustion engines, will perform on par if not better than existing choices. Tests are conducted to investigate the methods of fast battery charging and the challenges this technique creates. Attention is also given to the development of a pulsed Proton Exchange Membrane (PEM) fuel cell, specifically to prove whether pulse modulation is more efficient in a hydrogen producing fuel cell as opposed to direct-driven voltage and current alternatives.
Show less
Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3174313
Subject Headings: Power electronics, Digital control systems, Electric current converters, Fuel cells, Economic aspects
Format: Document (PDF)

Title: Approaches to object/relational database systems.
Creator: Vijayanagaram, Hemanth Kumar., Florida Atlantic University, Solomon, Martin K., Larrondo-Petrie, Maria M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In this thesis, we investigate the different proposed ways of combining object oriented and relational database systems (such combined systems are commonly called object-relational systems). This thesis is based on ideas presented in various papers about object and object relational databases. In this work, a discussion of standards such as ANSI's SQL3 (to be released) and ODMG-93 is given. In particular, the "Class = Relation" and "Class = Domain" approaches to object-relational systems are...
Show moreIn this thesis, we investigate the different proposed ways of combining object oriented and relational database systems (such combined systems are commonly called object-relational systems). This thesis is based on ideas presented in various papers about object and object relational databases. In this work, a discussion of standards such as ANSI's SQL3 (to be released) and ODMG-93 is given. In particular, the "Class = Relation" and "Class = Domain" approaches to object-relational systems are investigated. Arguments supporting the proposition that the latter approach is the correct approach are presented.
Show less
Date Issued: 1996
PURL: http://purl.flvc.org/fcla/dt/15350
Subject Headings: Object-oriented databases, Relational databases
Format: Document (PDF)

Title: Artificial Intelligence Based Electrical Impedance Tomography for Local Tissue.
Creator: Rao, Manasa, Pandya, Abhijit S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This research aims at proposing the use of Electrical Impedance Tomography (EIT), a non-invasive technique that makes it possible to measure two or three dimensional impedance of living local tissue in a human body which is applied for medical diagnosis of diseases. In order to achieve this, electrodes are attached to the part of human body and an image of the conductivity or permittivity of living tissue is deduced from surface electrodes. In this thesis we have worked towards alleviating...
Show moreThis research aims at proposing the use of Electrical Impedance Tomography (EIT), a non-invasive technique that makes it possible to measure two or three dimensional impedance of living local tissue in a human body which is applied for medical diagnosis of diseases. In order to achieve this, electrodes are attached to the part of human body and an image of the conductivity or permittivity of living tissue is deduced from surface electrodes. In this thesis we have worked towards alleviating drawbacks of EIT such as estimating parameters by incorporating it in an electrode structure and determining a solution to spatial distribution of bio-impedance to a close proximity. We address the issue of initial parameter estimation and spatial resolution accuracy of an electrode structure by using an arrangement called "divided electrode" for measurement of bio-impedance in a cross section of a local tissue. Its capability is examined by computer simulations, where a distributed equivalent circuit is utilized as a model for the cross section tissue. Further, a novel hybrid model is derived which is a combination of artificial intelligence based gradient free optimization technique and numerical integration in order to estimate parameters. This arne! iorates the achievement of spatial resolution of equivalent circuit model to the closest accuracy.
Show less
Date Issued: 2008
PURL: http://purl.flvc.org/fau/fd/FA00012544
Subject Headings: Electrical impedance tomography, Diagnostic imaging--Data processing, Computational intelligence
Format: Document (PDF)

Title: An artificial neural network architecture for interpolation, function approximation, time series modeling and control applications.
Creator: Luebbers, Paul Glenn., Florida Atlantic University, Pandya, Abhijit S., Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: A new artificial neural network architecture called Power Net (PWRNET) and Orthogonal Power Net (OPWRNET) has been developed. Based on the Taylor series expansion of the hyperbolic tangent function, this novel architecture can approximate multi-input multi-layer artificial networks, while requiring only a single layer of hidden nodes. This allows a compact network representation with only one layer of hidden layer weights. The resulting trained network can be expressed as a polynomial...
Show moreA new artificial neural network architecture called Power Net (PWRNET) and Orthogonal Power Net (OPWRNET) has been developed. Based on the Taylor series expansion of the hyperbolic tangent function, this novel architecture can approximate multi-input multi-layer artificial networks, while requiring only a single layer of hidden nodes. This allows a compact network representation with only one layer of hidden layer weights. The resulting trained network can be expressed as a polynomial function of the input nodes. Applications which cannot be implemented with conventional artificial neural networks, due to their intractable nature, can be developed with these network architectures. The degree of nonlinearity of the network can be directly controlled by adjusting the number of hidden layer nodes, thus avoiding problems of over-fitting which restrict generalization. The learning algorithm used for adapting the network is the familiar error back propagation training algorithm. Other learning algorithms may be applied and since only one hidden layer is to be trained, the training performance of the network is expected to be comparable to or better than conventional multi-layer feed forward networks. The new architecture is explored by applying OPWRNET to classification, function approximation and interpolation problems. These applications show that the OPWRNET has comparable performance to multi-layer perceptrons. The OPWRNET was also applied to the prediction of noisy time series and the identification of nonlinear systems. The resulting trained networks, for system identification tasks, can be expressed directly as discrete nonlinear recursive polynomials. This characteristic was exploited in the development of two new neural network based nonlinear control algorithms, the Linearized Self-Tuning Controller (LSTC) and a variation of a Neural Adaptive Controller (NAC). These control algorithms are compared to a linear self-tuning controller and an artificial neural network based Inverse Model Controller. The advantages of these new controllers are discussed.
Show less
Date Issued: 1994
PURL: http://purl.flvc.org/fcla/dt/12357
Subject Headings: Neural networks (Computer science)
Format: Document (PDF)

Title: ASSESSING METHODS AND TOOLS TO IMPROVE REPORTING, INCREASE TRANSPARENCY, AND REDUCE FAILURES IN MACHINE LEARNING APPLICATIONS IN HEALTHCARE.
Creator: Garbin, Christian, Marques, Oge, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description: Artificial intelligence (AI) had a few false starts – the AI winters of the 1970s and 1980s. We are now in what looks like an AI summer. There are many useful applications of AI in the field. But there are still unfulfilled promises and outright failures. From self-driving cars that work only in constrained cases, to medical image analysis products that would replace radiologists but never did, we still struggle to translate successful research into successful real-world applications. The...
Show moreArtificial intelligence (AI) had a few false starts – the AI winters of the 1970s and 1980s. We are now in what looks like an AI summer. There are many useful applications of AI in the field. But there are still unfulfilled promises and outright failures. From self-driving cars that work only in constrained cases, to medical image analysis products that would replace radiologists but never did, we still struggle to translate successful research into successful real-world applications. The software engineering community has accumulated a large body of knowledge over the decades on how to develop, release, and maintain products. AI products, being software products, benefit from some of that accumulated knowledge, but not all of it. AI products diverge from traditional software products in fundamental ways: their main component is not a specific piece of code, written for a specific purpose, but a generic piece of code, a model, customized by a training process driven by hyperparameters and a dataset. Datasets are usually large and models are opaque. We cannot directly inspect them as we can inspect the code of traditional software products. We need other methods to detect failures in AI products.
Show less
Date Issued: 2020
PURL: http://purl.flvc.org/fau/fd/FA00013580
Subject Headings: Machine learning, Artificial intelligence, Healthcare
Format: Document (PDF)

Title: Asset identification using image descriptors.
Creator: Friedel, Reena Ursula., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Asset management is a time consuming and error prone process. Information Technology (IT) personnel typically perform this task manually by visually inspecting assets to identify misplaced assets. If this process is automated and provided to IT personnel it would prove very useful in keeping track of assets in a server rack. A mobile based solution is proposed to automate this process. The asset management application on the tablet captures images of assets and searches an annotated database...
Show moreAsset management is a time consuming and error prone process. Information Technology (IT) personnel typically perform this task manually by visually inspecting assets to identify misplaced assets. If this process is automated and provided to IT personnel it would prove very useful in keeping track of assets in a server rack. A mobile based solution is proposed to automate this process. The asset management application on the tablet captures images of assets and searches an annotated database to identify the asset. We evaluate the matching performance and speed of asset matching using three different image feature descriptors. Methods to reduce feature extraction and matching complexity were developed. Performance and accuracy tradeoffs were studied, domain specific problems were identified, and optimizations for mobile platforms were made. The results show that the proposed methods reduce complexity of asset matching by 67% when compared to the matching process using unmodified image feature descriptors.
Show less
Date Issued: 2012
PURL: http://purl.flvc.org/FAU/3342051
Subject Headings: Data mining, Technological innovations, Mobile computing, User-centered system design, Application software, Development
Format: Document (PDF)

Title: Augmented reality methods and algorithms for hearing augmentation.
Creator: Carmigniani, Julie., Charles E. Schmidt College of Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: While new technologies are often used to facilitate regular people's lives, they often fail to see their potential in helping disabled people. Augmented reality, one of the newest state-of-the-art technologies, offers users the opportunity to add virtual information to their real world surroundings in real time. It also has the potential to not only augment the sense of sight, but also other senses such as hearing. Augmented reality could be used to offer the opportunity to complement users'...
Show moreWhile new technologies are often used to facilitate regular people's lives, they often fail to see their potential in helping disabled people. Augmented reality, one of the newest state-of-the-art technologies, offers users the opportunity to add virtual information to their real world surroundings in real time. It also has the potential to not only augment the sense of sight, but also other senses such as hearing. Augmented reality could be used to offer the opportunity to complement users' missing sense. In this thesis, we study augmented reality technologies, systems and applications, and suggest the future of AR applications. We explain how to integrate augmented reality into iOS applications and propose an augmented reality application for hearing augmentation using an iPad2. We believe mobile devices are the best platform for augmented reality as they are widespread and their computational power is rapidly growing to be able to handle true AR applications.
Show less
Date Issued: 2011
PURL: http://purl.flvc.org/FAU/3332178
Subject Headings: Mobile communication systems, Augmented reality, Computer graphics, Virtual reality, Human-computer interaction, User interfaces (Computer systems), Application software, Development
Format: Document (PDF)

Title: An authorization model for object-oriented and semantic databases.
Creator: Song, Haiyan., Florida Atlantic University, Fernandez, Eduardo B., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The incorporation of object-oriented and semantic modeling concepts to databases is one of the most significant advances in the evolution of database systems. Among the many issues brought along by this integration, one that becomes important is the protection of the information. This thesis presents an authorization model that applies two basic aspects: control of users' access to data values, and control of administrators' access to data definitions and authorization rules. The model...
Show moreThe incorporation of object-oriented and semantic modeling concepts to databases is one of the most significant advances in the evolution of database systems. Among the many issues brought along by this integration, one that becomes important is the protection of the information. This thesis presents an authorization model that applies two basic aspects: control of users' access to data values, and control of administrators' access to data definitions and authorization rules. The model consists of a set of policies, a structure for authorization rules, algorithms for access request validation and procedures for administrative functions. Even though this model is developed in the context of a particular data model, the discussion is sufficiently general and can be applied to similar environments.
Show less
Date Issued: 1990
PURL: http://purl.flvc.org/fcla/dt/14592
Subject Headings: Object-oriented databases, Data base security, Computers--Access control
Format: Document (PDF)

Title: Automated biometrics of audio-visual multiple modals.
Creator: Huang, Lin, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Biometrics is the science and technology of measuring and analyzing biological data for authentication purposes. Its progress has brought in a large number of civilian and government applications. The candidate modalities used in biometrics include retinas, fingerprints, signatures, audio, faces, etc. There are two types of biometric system: single modal systems and multiple modal systems. Single modal systems perform person recognition based on a single biometric modality and are affected by...
Show moreBiometrics is the science and technology of measuring and analyzing biological data for authentication purposes. Its progress has brought in a large number of civilian and government applications. The candidate modalities used in biometrics include retinas, fingerprints, signatures, audio, faces, etc. There are two types of biometric system: single modal systems and multiple modal systems. Single modal systems perform person recognition based on a single biometric modality and are affected by problems like noisy sensor data, intra-class variations, distinctiveness and non-universality. Applying multiple modal systems that consolidate evidence from multiple biometric modalities can alleviate those problems of single modal ones. Integration of evidence obtained from multiple cues, also known as fusion, is a critical part in multiple modal systems, and it may be consolidated at several levels like feature fusion level, matching score fusion level and decision fusion level. Among biometric modalities, both audio and face modalities are easy to use and generally acceptable by users. Furthermore, the increasing availability and the low cost of audio and visual instruments make it feasible to apply such Audio-Visual (AV) systems for security applications. Therefore, this dissertation proposes an algorithm of face recognition. In addition, it has developed some novel algorithms of fusion in different levels for multiple modal biometrics, which have been tested by a virtual database and proved to be more reliable and robust than systems that rely on a single modality.
Show less
Date Issued: 2010
PURL: http://purl.flvc.org/FAU/1927864
Subject Headings: Pattern recognition systems, Optical pattern recognition, Biometric identification, Identification, Automation, Automatic speech recognition
Format: Document (PDF)

Title: Automated control of microfluidics devices.
Creator: Gerstel, Ian., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In order for microfluidics devices to be marketable, they must be inexpensive and easy to use. Two projects were pursued in this study for this purpose. The first was the design of a chip alignment system for visual feedback, in which a two-layer microfluidic chip was placed under a camera and an image processing and linear algebra program aligned a computer model to it. The system then translated the new locations of air valves and could detect valve activation in a chip filled with food...
Show moreIn order for microfluidics devices to be marketable, they must be inexpensive and easy to use. Two projects were pursued in this study for this purpose. The first was the design of a chip alignment system for visual feedback, in which a two-layer microfluidic chip was placed under a camera and an image processing and linear algebra program aligned a computer model to it. The system then translated the new locations of air valves and could detect valve activation in a chip filled with food coloring. The second was the design of a cheap, portable system to detect phosphorus in water. This system could not be completed due to time constraints, but the methods were detailed, and design ideas were laid out for future work.
Show less
Date Issued: 2010
PURL: http://purl.flvc.org/FAU/3158764
Subject Headings: Microfluidics, Design, Microelectromagnetical systems, Design, Fluidic devices, Design, Micromechanics
Format: Document (PDF)

Title: Automated nursing knowledge classification using indexing.
Creator: Chinchanikar, Sucharita Vijay., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Promoting healthcare and wellbeing requires the dedication of a multi-tiered health service delivery system, which is comprised of specialists, medical doctors and nurses. A holistic view to a patient care perspective involves emotional, mental and physical healthcare needs, in which caring is understood as the essence of nursing. Properly and efficiently capturing and managing nursing knowledge is essential to advocating health promotion and illness prevention. This thesis proposes a...
Show morePromoting healthcare and wellbeing requires the dedication of a multi-tiered health service delivery system, which is comprised of specialists, medical doctors and nurses. A holistic view to a patient care perspective involves emotional, mental and physical healthcare needs, in which caring is understood as the essence of nursing. Properly and efficiently capturing and managing nursing knowledge is essential to advocating health promotion and illness prevention. This thesis proposes a document-indexing framework for automating classification of nursing knowledge based on nursing theory and practice model. The documents defining the numerous categories in nursing care model are structured with the help of expert nurse practitioners and professionals. These documents are indexed and used as a benchmark for the process of automatic mapping of each expression in the assessment form of a patient to the corresponding category in the nursing theory model. As an illustration of the proposed methodology, a prototype application is developed using the Latent Semantic Indexing (LSI) technique. The prototype application is tested in a nursing practice environment to validate the accuracy of the proposed algorithm. The simulation results are also compared with an application using Lucene indexing technique that internally uses modified vector space model for indexing. The result comparison showed that the LSI strategy gives 87.5% accurate results compared to the Lucene indexing technique that gives 80% accuracy. Both indexing methods maintain 100% consistency in the results.
Show less
Date Issued: 2009
PURL: http://purl.flvc.org/FAU/186677
Subject Headings: Nursing, Computer-assisted instruction, Data transmission systems, Outcome assessment (Medical care), Nursing assessment, Digital techniques
Format: Document (PDF)

Title: Automatic extraction and tracking of eye features from facial image sequences.
Creator: Xie, Xangdong., Florida Atlantic University, Sudhakar, Raghavan, Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The dual issues of extracting and tracking eye features from video images are addressed in this dissertation. The proposed scheme is different from conventional intrusive eye movement measuring system and can be implemented using an inexpensive personal computer. The desirable features of such a measurement system are low cost, accuracy, automated operation, and non-intrusiveness. An overall scheme is presented for which a new algorithm is forwarded for each of the function blocks in the...
Show moreThe dual issues of extracting and tracking eye features from video images are addressed in this dissertation. The proposed scheme is different from conventional intrusive eye movement measuring system and can be implemented using an inexpensive personal computer. The desirable features of such a measurement system are low cost, accuracy, automated operation, and non-intrusiveness. An overall scheme is presented for which a new algorithm is forwarded for each of the function blocks in the processing system. A new corner detection algorithm is presented in which the problem of detecting corners is solved by minimizing a cost function. Each cost factor captures a desirable characteristic of the corner using both the gray level information and the geometrical structure of a corner. This approach additionally provides corner orientations and angles along with corner locations. The advantage of the new approach over the existing corner detectors is that it is able to improve the reliability of detection and localization by imposing criteria related to both the gray level data and the corner structure. The extraction of eye features is performed by using an improved method of deformable templates which are geometrically arranged to resemble the expected shape of the eye. The overall energy function is redefined to simplify the minimization process. The weights for the energy terms are selected based on the normalized value of the energy term. Thus the weighting schedule of the modified method does not demand any expert knowledge for the user. Rather than using a sequential procedure, all parameters of the template are changed simultaneously during the minimization process. This reduces not only the processing time but also the probability of the template being trapped in local minima. An efficient algorithm for real-time eye feature tracking from a sequence of eye images is developed in the dissertation. Based on a geometrical model which describes the characteristics of the eye, the measurement equations are formulated to relate suitably selected measurements to the tracking parameters. A discrete Kalman filter is then constructed for the recursive estimation of the eye features, while taking into account the measurement noise. The small processing time allows this tracking algorithm to be used in real-time applications. This tracking algorithm is suitable for an automated, non-intrusive and inexpensive system as the algorithm is capable of measuring the time profiles of the eye movements. The issue of compensating head movements during the tracking of eye movements is also discussed. An appropriate measurement model was established to describe the effects of head movements. Based on this model, a Kalman filter structure was formulated to carry out the compensation. The whole tracking scheme which cascades two Kalman filters is constructed to track the iris movement, while compensating the head movement. The presence of the eye blink is also taken into account and its detection is incorporated into the cascaded tracking scheme. The above algorithms have been integrated to design an automated, non-intrusive and inexpensive system which provides accurate time profile of eye movements tracking from video image frames.
Show less
Date Issued: 1994
PURL: http://purl.flvc.org/fcla/dt/12377
Subject Headings: Kalman filtering, Eye--Movements, Algorithms, Image processing
Format: Document (PDF)

FAU Theses and Dissertations (735)	+ -
FAU College Collections (9)	+ -

Wireless communication systems (57)	+ -
Neural networks (Computer science) (42)	+ -
Computer network protocols (35)	+ -
Machine learning (34)	+ -
Computer software--Quality control (27)	+ -

Technological innovations (27)	+ -
Computer algorithms (24)	+ -
Computer networks (24)	+ -
Software engineering (22)	+ -
Pattern recognition systems (21)	+ -
Computer architecture (20)	+ -
Fault-tolerant computing (20)	+ -
Mobile communication systems (20)	+ -
Algorithms (19)	+ -
Computer network architectures (18)	+ -
Expert systems (Computer science) (18)	+ -
Artificial intelligence (17)	+ -
Data mining (17)	+ -
Mobile computing (17)	+ -
Computer security (15)	+ -
Digital techniques (15)	+ -
Image processing--Digital techniques (15)	+ -
Data transmission systems (14)	+ -
Image processing (14)	+ -
Mathematical models (14)	+ -
Sensor networks (14)	+ -
Security measures (13)	+ -
Signal processing (13)	+ -
Software measurement (13)	+ -
Big data (12)	+ -

Android (Electronic resource). (2)	+ -
Android. (1)	+ -
Linux. (1)	+ -
OPNET. (1)	+ -

Electronic Thesis or Dissertation (735)	+ -
Program Review (9)	+ -

Search In

Pages

Pages

Sort Results By:

Narrow results by:

Collection

Topical Subject

Geographic Subject

Title as Subject

Genre

Type of Resource

Language

Creator

Format

Owner