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- Title
- Submicron CAD design and analysis of MOS Current Mirrors.
- Creator
- Rivas-Torres, Wilfredo, Florida Atlantic University, Roth, Zvi S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Current Mirrors are widely used circuits in IC designs. They are used as current sources and loads. The proper selection of a Current Mirror configuration is therefore important. This thesis reviews critical parameters for Current Minors characterization. Six MOS Current Mirror configurations are studied, and their performance characteristics are compared. The proper selection and use of MOSFET models are presented. It is shown that CAD-based design and analysis is indispensable if realistic...
Show moreCurrent Mirrors are widely used circuits in IC designs. They are used as current sources and loads. The proper selection of a Current Mirror configuration is therefore important. This thesis reviews critical parameters for Current Minors characterization. Six MOS Current Mirror configurations are studied, and their performance characteristics are compared. The proper selection and use of MOSFET models are presented. It is shown that CAD-based design and analysis is indispensable if realistic MOS models such as BSIM3 are used. The CAD based analysis and design employs simulation parameter tuning, optimization and swept parameters. The presented CAD techniques allow a designer to make important tradeoffs for different configurations. One of the main thesis observations is that it is not always necessary to use more involved Current Mirror configurations; a Simple Current Mirror Configuration is often sufficient. The thesis also studies the adverse effects on the design caused by process variations.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13119
- Subject Headings
- Metal oxide semiconductors--Computer-aided design, Integrated circuits, Metal oxide semiconductor field-effect transistors
- Format
- Document (PDF)
- Title
- Mobility management in voice over IP networks.
- Creator
- Sugunan, Shiby., Florida Atlantic University, Ilyas, Mohammad, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Wireless Internet access has recently gained significant attention as wireless/mobile communications and networking become widespread. Voice over IP service is likely to play a key role in the convergence of IP based Internet and mobile cellular networks. The mobility management performance for Mobile IP and Session Initiation Protocol is the focus of this thesis. After illustrating the operation of the protocols, the discrete event simulator, Network Simulator 2 (ns2), is used to compare the...
Show moreWireless Internet access has recently gained significant attention as wireless/mobile communications and networking become widespread. Voice over IP service is likely to play a key role in the convergence of IP based Internet and mobile cellular networks. The mobility management performance for Mobile IP and Session Initiation Protocol is the focus of this thesis. After illustrating the operation of the protocols, the discrete event simulator, Network Simulator 2 (ns2), is used to compare the performance of the two protocols. The comparison of the protocols is done by comparing average end-to-end delay and the ratio of the number of packets received to the number of packets originally sent (Packet Delivery Fraction). The impact of mobility is analyzed by studying the performance of the protocols, for various mobility scenarios. The effect of an increase in the number of nodes and increase in velocity of the mobile node on the performance of the Mobile IP and SIP is compared. The performance of the Mobile IP and SIP is compared by measuring the performance metrics of the two protocols for similar simulations. The results obtained as a result of the simulations leads us to some interesting conclusions.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13113
- Subject Headings
- Internet telephony, Wireless Internet, Mobile computing, TCP/IP (Computer network protocol)
- Format
- Document (PDF)
- Title
- Performance analysis of K-means algorithm and Kohonen networks.
- Creator
- Syed, Afzal A., Florida Atlantic University, Pandya, Abhijit S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
K-means algorithm and Kohonen network possess self-organizing characteristics and are widely used in different fields currently. The factors that influence the behavior of K-means are the choice of initial cluster centers, number of cluster centers and the geometric properties of the input data. Kohonen networks have the ability of self-organization without any prior input about the number of clusters to be formed. This thesis looks into the performances of these algorithms and provides a...
Show moreK-means algorithm and Kohonen network possess self-organizing characteristics and are widely used in different fields currently. The factors that influence the behavior of K-means are the choice of initial cluster centers, number of cluster centers and the geometric properties of the input data. Kohonen networks have the ability of self-organization without any prior input about the number of clusters to be formed. This thesis looks into the performances of these algorithms and provides a unique way of combining them for better clustering. A series of benchmark problem sets are developed and run to obtain the performance analysis of the K-means algorithm and Kohonen networks. We have attempted to obtain the better of these two self-organizing algorithms by providing the same problem sets and extract the best results based on the users needs. A toolbox, which is user-friendly and written in C++ and VC++ is developed for applications on both images and feature data sets. The tool contains K-means algorithm and Kohonen networks code for clustering and pattern classification.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13112
- Subject Headings
- Self-organizing maps, Neural networks (Computer science), Cluster analysis--Computer programs, Computer algorithms
- Format
- Document (PDF)
- Title
- Techniques for combining binary classifiers: A comparative study in network intrusion detection systems.
- Creator
- Lin, Hua., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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We discuss a set of indirect combining techniques for addressing multi-category classification problems that have been used in many domains, but not for intrusion detection systems. In contrast to the indirect combining techniques, direct techniques generally extend associated binary classifiers to handle multi-category classification problems. An indirect combining technique decomposes the original multi-category problem into, based on some criteria, multiple binary-category problems. We...
Show moreWe discuss a set of indirect combining techniques for addressing multi-category classification problems that have been used in many domains, but not for intrusion detection systems. In contrast to the indirect combining techniques, direct techniques generally extend associated binary classifiers to handle multi-category classification problems. An indirect combining technique decomposes the original multi-category problem into, based on some criteria, multiple binary-category problems. We investigated two different approaches for building the binary classifiers. The results of the binary classifiers are then merged using a combining technique---three different combining techniques were studied. We implement some of the indirect combining techniques proposed in recent literature, and apply them to a case study of the DARPA KDD-1999 network intrusion detection project. The results demonstrate the usefulness of using indirect combining techniques for the multi-category classification problem of intrusion detection systems.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13111
- Subject Headings
- Computer networks--Security measures, Computer security, Computers--Access control, Electronic countermeasures, Fuzzy systems
- 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
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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.
Show less - 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
- A case study: Performance enhancement of nonlinear combinational optimization problem by neural networks.
- Creator
- Soni, Saurabh., Florida Atlantic University, Pandya, Abhijit S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Artificial Neural Networks have been widely used for obtaining solutions for combinational optimization problems. Traveling Salesman problem is a well known nonlinear combinational optimization problem. In Traveling Salesman problem, a fixed number of cities is given. An optimal tour of all these cities is required such that each city is visited only once and the total tour distance to be covered has to be minimized. Hopfield Networks have been applied for generating an optimal solution....
Show moreArtificial Neural Networks have been widely used for obtaining solutions for combinational optimization problems. Traveling Salesman problem is a well known nonlinear combinational optimization problem. In Traveling Salesman problem, a fixed number of cities is given. An optimal tour of all these cities is required such that each city is visited only once and the total tour distance to be covered has to be minimized. Hopfield Networks have been applied for generating an optimal solution. However there are certain factors which result in instability and local optimization of Hopfield Networks. In such cases the solutions obtained may not be optimal and feasible. In this thesis, the application of the K-Means algorithm is combined with the Hopfield Networks to generate more stable and optimum solutions to traveling salesperson problem.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13108
- Subject Headings
- Neural networks (Computer science), Traveling-salesman problem
- Format
- Document (PDF)
- Title
- Multiplayer mobile gaming support in JAVA 2 Micro Edition.
- Creator
- Maksimovic, Predrag., Florida Atlantic University, Mahgoub, Imad, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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The thesis proposes a new Java Application Programming Interface (API) for developing multiplayer mobile games. The proposed API is organized in such a way that it can easily be integrated with the existing suite of APIs defined in the Java 2 Micro Edition (J2ME)---the Java edition that specifically targets mobile devices. The proposed API provides J2ME programmers with components that simplify multiplayer mobile game development process. The main idea of the API is to encapsulate low-level...
Show moreThe thesis proposes a new Java Application Programming Interface (API) for developing multiplayer mobile games. The proposed API is organized in such a way that it can easily be integrated with the existing suite of APIs defined in the Java 2 Micro Edition (J2ME)---the Java edition that specifically targets mobile devices. The proposed API provides J2ME programmers with components that simplify multiplayer mobile game development process. The main idea of the API is to encapsulate low-level technical details associated with establishing and maintaining communication links between mobile devices. A programmer who uses the API is only concerned with the high-level multiplayer aspects of programming such as managing game players and sessions. The actual implementation of the API on each target device is responsible for utilizing the supported underlying network protocols such as the Bluetooth, HTTP and IEEE 802.11b.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13106
- Subject Headings
- JAVA (Computer program language), Computer games--Programming
- Format
- Document (PDF)
- Title
- A comparative study of classification algorithms for network intrusion detection.
- Creator
- Wang, Yunling., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
As network-based computer systems play increasingly vital roles in modern society, they have become the targets of criminals. Network security has never been more important a subject than in today's extensively interconnected computer world. Intrusion Detection Systems (IDS) have been used along with the data mining techniques to detect intrusions. In this thesis, we present a comparative study of intrusion detection using a decision-tree learner (C4.5), two rule-based learners (ripper and...
Show moreAs network-based computer systems play increasingly vital roles in modern society, they have become the targets of criminals. Network security has never been more important a subject than in today's extensively interconnected computer world. Intrusion Detection Systems (IDS) have been used along with the data mining techniques to detect intrusions. In this thesis, we present a comparative study of intrusion detection using a decision-tree learner (C4.5), two rule-based learners (ripper and ridor), a learner to combine decision trees and rules (PART), and two instance-based learners (IBK and Nnge). We investigate and compare the performance of IDSs based on the six techniques, with respect to a case study of the DAPAR KDD-1999 network intrusion detection project. Investigation results demonstrated that data mining techniques are very useful in the area of intrusion detection.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13102
- Subject Headings
- Computer networks--Security measures, Data mining, Decision trees
- Format
- Document (PDF)
- Title
- Binary representation of DNA sequences towards developing useful algorithms in bioinformatic data-mining.
- Creator
- Pandya, Shivani., 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 refers to a research addressing the use of binary representation of the DNA for the purpose of developing useful algorithms for Bioinformatics. Pertinent studies address the use of a binary form of the DNA base chemicals in information-theoretic base so as to identify symmetry between DNA and complementary DNA. This study also refers to "fuzzy" (codon-noncodon) considerations in delinating codon and noncodon regimes in a DNA sequences. The research envisaged further includes a...
Show moreThis thesis refers to a research addressing the use of binary representation of the DNA for the purpose of developing useful algorithms for Bioinformatics. Pertinent studies address the use of a binary form of the DNA base chemicals in information-theoretic base so as to identify symmetry between DNA and complementary DNA. This study also refers to "fuzzy" (codon-noncodon) considerations in delinating codon and noncodon regimes in a DNA sequences. The research envisaged further includes a comparative analysis of the test results on the aforesaid efforts using different statistical metrics such as Hamming distance Kullback-Leibler measure etc. the observed details supports the symmetry aspect between DNA and CDNA strands. It also demonstrates capability of identifying non-codon regions in DNA even under diffused (overlapped) fuzzy states.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/13089
- Subject Headings
- Bioinformatics, Data mining, Nucleotide sequence--Databases, Computer algorithms
- Format
- Document (PDF)
- Title
- A study of Internet-based control of processes.
- Creator
- Popescu, Cristian., Florida Atlantic University, Zhuang, Hanqi, Wang, Yuan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
In certain applications, one needs to control physical plants that operate in hazardous conditions. In such situations, it is necessary to acquire access to the controller from a different (remote) location through data communication networks, in order to interconnect the remote location and the controller. The use of such network linking between the plant and the controller may introduce network delays, which would affect adversely the performance of the process control. The main theoretical...
Show moreIn certain applications, one needs to control physical plants that operate in hazardous conditions. In such situations, it is necessary to acquire access to the controller from a different (remote) location through data communication networks, in order to interconnect the remote location and the controller. The use of such network linking between the plant and the controller may introduce network delays, which would affect adversely the performance of the process control. The main theoretical contribution of this thesis is to answer the following question: How large can a network delay be tolerated such that the delayed closed-loop system is locally asymptotically stable? An explicit time-independent bound for the delay is derived. In addition, various practical realizations for the remote control tasks are presented, utilizing a set of predefined classes for serial communication, data-acquisition modules and stream-based sockets. Due to the presence of a network, implementing an efficient control scheme is a not trivial problem. Hence, two practical frameworks for Internet-based control are illustrated in this thesis. Related implementation issues are addressed in detail. Examples and case studies are provided to demonstrate the effectiveness of the proposal approach.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/13073
- Subject Headings
- Time delay systems, Process control, Computer networks--Remote access, World Wide Web
- Format
- Document (PDF)
- Title
- Survey of design techniques for signal integrity.
- Creator
- Karnati, Raghuveer., Florida Atlantic University, Shankar, Ravi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Signal Integrity is a major bottleneck for DSM designs. Signal integrity refers to wide variety of problems, which leads to misconception. Signal integrity causes delay or noise at the high-level, but this boils down to resistance, capacitance and inductance (RLC) at circuit level. Several analysis and reduction techniques were proposed for reducing these effects on signal integrity. This work solves the misconception by encompassing different problems Chat effect signal integrity and can be...
Show moreSignal Integrity is a major bottleneck for DSM designs. Signal integrity refers to wide variety of problems, which leads to misconception. Signal integrity causes delay or noise at the high-level, but this boils down to resistance, capacitance and inductance (RLC) at circuit level. Several analysis and reduction techniques were proposed for reducing these effects on signal integrity. This work solves the misconception by encompassing different problems Chat effect signal integrity and can be good reference for a integrated circuit designer. The objective is to analyze these modeling methods, reduction techniques, tools and make recommendations that aids in developing a methodology for perfect design closure with an emphasis on signal integrity. These recommendations would form a basis for developing a methodology to analyze interference effects at higher levels of abstraction.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/13065
- Subject Headings
- Integrated circuits--Design and construction, Signal processing, Electronic circuit design
- 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
- Financial prediction using time series.
- Creator
- Srinivasan, Arunkumar., Florida Atlantic University, Pandya, Abhijit S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This thesis discusses the implementation of a feed forward NN using time series model to predict the sudden rise or sudden crash of a company's stock prices. The theory behind this prediction system is Pattern recognition. Pattern recognition techniques for time-series prediction are based on structural matching of the current state of the time-series with previously occurring states in historical data for making predictions. This study reports the result of attempts to predict the Motorola...
Show moreThis thesis discusses the implementation of a feed forward NN using time series model to predict the sudden rise or sudden crash of a company's stock prices. The theory behind this prediction system is Pattern recognition. Pattern recognition techniques for time-series prediction are based on structural matching of the current state of the time-series with previously occurring states in historical data for making predictions. This study reports the result of attempts to predict the Motorola stock price index using artificial neural networks (ANN). Daily data from January 1999 to December 2001 were taken from the NYSE. These data are classified based on criteria of an n% fall or rise of price corresponding to the previous day close price. A novel method using Hurst exponent is used in selecting the data set. These data are fed into a Back Propagated Neural Network. The number of hidden layers and number of neurons are systematically selected to implement a better predicting machine. The implemented model is tested using both interpolated and extrapolated data. Fundamental limitations and inherent difficulties when using neural networks for processing of high noise, small sample size signals are also discussed. Results of the prediction are presented and an elaborate discussion is made comparing the results.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/13045
- Subject Headings
- Pattern recognition systems, Neural networks (Computer science), Stock exchanges
- Format
- Document (PDF)
- Title
- TACKLING BIAS, PRIVACY, AND SCARCITY CHALLENGES IN HEALTH DATA ANALYTICS.
- Creator
- Wang, Shuwen, Zhu, Xingquan, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
Health data analysis has emerged as a critical domain with immense potential to revolutionize healthcare delivery, disease management, and medical research. However, it is confronted by formidable challenges, including sample bias, data privacy concerns, and the cost and scarcity of labeled data. These challenges collectively impede the development of accurate and robust machine learning models for various healthcare applications, from disease diagnosis to treatment recommendations. Sample...
Show moreHealth data analysis has emerged as a critical domain with immense potential to revolutionize healthcare delivery, disease management, and medical research. However, it is confronted by formidable challenges, including sample bias, data privacy concerns, and the cost and scarcity of labeled data. These challenges collectively impede the development of accurate and robust machine learning models for various healthcare applications, from disease diagnosis to treatment recommendations. Sample bias and specificity refer to the inherent challenges in working with health datasets that may not be representative of the broader population or may exhibit disparities in their distributions. These biases can significantly impact the generalizability and effectiveness of machine learning models in healthcare, potentially leading to suboptimal outcomes for certain patient groups. Data privacy and locality are paramount concerns in the era of digital health records and wearable devices. The need to protect sensitive patient information while still extracting valuable insights from these data sources poses a delicate balancing act. Moreover, the geographic and jurisdictional differences in data regulations further complicate the use of health data in a global context. Label cost and scarcity pertain to the often labor-intensive and expensive process of obtaining ground-truth labels for supervised learning tasks in healthcare. The limited availability of labeled data can hinder the development and deployment of machine learning models, particularly in specialized medical domains.
Show less - Date Issued
- 2023
- PURL
- http://purl.flvc.org/fau/fd/FA00014336
- Subject Headings
- Data analytics, Data mining, Ensemble learning (Machine learning), Machine learning, Health
- Format
- Document (PDF)
- Title
- OCR2SEQ: A NOVEL MULTI-MODAL DATA AUGMENTATION PIPELINE FOR WEAK SUPERVISION.
- Creator
- Lowe, Michael A., Khoshgoftaar, Taghi M., Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
With the recent large-scale adoption of Large Language Models in multidisciplinary research and commercial space, the need for large amounts of labeled data has become more crucial than ever to evaluate potential use cases for opportunities in applied intelligence. Most domain specific fields require a substantial shift that involves extremely large amounts of heterogeneous data to have meaningful impact on the pre-computed weights of most large language models. We explore extending the...
Show moreWith the recent large-scale adoption of Large Language Models in multidisciplinary research and commercial space, the need for large amounts of labeled data has become more crucial than ever to evaluate potential use cases for opportunities in applied intelligence. Most domain specific fields require a substantial shift that involves extremely large amounts of heterogeneous data to have meaningful impact on the pre-computed weights of most large language models. We explore extending the capabilities a state-of-the-art unsupervised pre-training method; Transformers and Sequential Denoising Auto-Encoder (TSDAE). In this study we show various opportunities for using OCR2Seq a multi-modal generative augmentation strategy to further enhance and measure the quality of noise samples used when using TSDAE as a pretraining task. This study is a first of its kind work that leverages converting both generalized and sparse domains of relational data into multi-modal sources. Our primary objective is measuring the quality of augmentation in relation to the current implementation of the sentence transformers library. Further work includes the effect on ranking, language understanding, and corrective quality.
Show less - Date Issued
- 2023
- PURL
- http://purl.flvc.org/fau/fd/FA00014367
- Subject Headings
- Natural language processing (Computer science), Deep learning (Machine learning)
- Format
- Document (PDF)
- Title
- OPTIMIZATION OF DATA ACQUISITION IN OPTICAL TOMOGRAPHY BASED ON ESTIMATION THEORY.
- Creator
- Javidan, Mahshad, Pashaie, Ramin, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
In any experimental platform, data acquisition is the first and essential step, and occasionally the most time-consuming and costly operation. During the process of data acquisition, we conduct experiments to measure the response of the system to a set of inputs. Methods of optimal design of experiment can be used to determine the most informative measurements and avoid numerous traps that trial-and-error experimentation might cause. In this research, we have developed a general approach for...
Show moreIn any experimental platform, data acquisition is the first and essential step, and occasionally the most time-consuming and costly operation. During the process of data acquisition, we conduct experiments to measure the response of the system to a set of inputs. Methods of optimal design of experiment can be used to determine the most informative measurements and avoid numerous traps that trial-and-error experimentation might cause. In this research, we have developed a general approach for designing optimal experiments, subsequently applying it to the domain of optical tomography. Optical tomography is a vital technology that enables three-dimensional imaging by reconstructing images from two-dimensional projections. This technology has applications across various fields, including medicine and material science. The process involves two main phases: data acquisition and image reconstruction. The traditional raster scanning method has been the standard approach for data acquisition, but it presents challenges in terms of scanning speed, quality, and exposure to harmful radiations in some cases. This has prompted researchers to explore ways to optimize the scanning process.
Show less - Date Issued
- 2023
- PURL
- http://purl.flvc.org/fau/fd/FA00014350
- Subject Headings
- Optical tomography, Data Collection, Estimation theory
- Format
- Document (PDF)
- Title
- DEVELOPMENT OF A WEARABLE DEVICE FOR MONITORING PHYSIOLOGICAL PARAMETERS RELATED TO HEART FAILURE.
- Creator
- Iqbal, Sheikh Muhammad Asher, Asghar, Waseem, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
-
Heart failure is a chronic cardiovascular disease that is caused due to the lack of blood supply from heart. This lack of blood supply leads to accumulation of the fluid in the thoracic region. Traditionally, implantable cardioverter defibrillators (ICDs) are used to treat HF and to monitor its parameters. Healthcare wearable devices (HWDs) are healthcare devices that can be worn or attached to the skin. HWD are non-invasive and low-cost means of providing healthcare at the point-of-care (POC...
Show moreHeart failure is a chronic cardiovascular disease that is caused due to the lack of blood supply from heart. This lack of blood supply leads to accumulation of the fluid in the thoracic region. Traditionally, implantable cardioverter defibrillators (ICDs) are used to treat HF and to monitor its parameters. Healthcare wearable devices (HWDs) are healthcare devices that can be worn or attached to the skin. HWD are non-invasive and low-cost means of providing healthcare at the point-of-care (POC). Herein, this dissertation discusses the development of a HWD for the monitoring of the parameters of heart failure (HF). These parameters include thoracic impedance, electrocardiogram (ECG), heart rate, oxygen saturation in blood and activity status of the subject. These are similar parameters as monitored using ICD. The dissertation will discuss the development, design, and results of the HWD.
Show less - Date Issued
- 2023
- PURL
- http://purl.flvc.org/fau/fd/FA00014349
- Subject Headings
- Wearable technology--Design and construction, Wearable devices, Heart failure
- Format
- Document (PDF)
- Title
- A comprehensive comparative study of multiple classification techniques for software quality estimation.
- Creator
- Puppala, Kishore., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Reliability and quality are desired features in industrial software applications. In some cases, they are absolutely essential. When faced with limited resources, software project managers will need to allocate such resources to the most fault prone areas. The ability to accurately classify a software module as fault-prone or not fault-prone enables the manager to make an informed resource allocation decision. An accurate quality classification avoids wasting resources on modules that are not...
Show moreReliability and quality are desired features in industrial software applications. In some cases, they are absolutely essential. When faced with limited resources, software project managers will need to allocate such resources to the most fault prone areas. The ability to accurately classify a software module as fault-prone or not fault-prone enables the manager to make an informed resource allocation decision. An accurate quality classification avoids wasting resources on modules that are not fault-prone. It also avoids missing the opportunity to correct faults relatively early in the development cycle, when they are less costly. This thesis seeks to introduce the classification algorithms (classifiers) that are implemented in the WEKA software tool. WEKA (Waikato Environment for Knowledge Analysis) was developed at the University of Waikato in New Zealand. An empirical investigation is performed using a case study at a real-world system.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/13039
- Subject Headings
- Software engineering, Computer software--Quality control, Decision trees
- Format
- Document (PDF)
- Title
- RSSI-BASED PASSIVE LOCALIZATION IN COMPLEX OUTDOOR ENVIRONMENTS USING WI-FI PROBE REQUESTS.
- Creator
- Bao, Fanchen, Hallstrom, Jason O., Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Capturing pedestrian mobility patterns with high fidelity provides a foundation for data-driven decision-making in support of city planning, emergency response, and more. Due to scalability requirements and the sensitive nature of studying pedestrian movements in public spaces, the methods involved must be passive, low-cost, and privacy-centric. Pedestrian localization based on Received Signal Strength Indicator (RSSI) measurements from Wi-Fi probe requests is a promising approach. Probe...
Show moreCapturing pedestrian mobility patterns with high fidelity provides a foundation for data-driven decision-making in support of city planning, emergency response, and more. Due to scalability requirements and the sensitive nature of studying pedestrian movements in public spaces, the methods involved must be passive, low-cost, and privacy-centric. Pedestrian localization based on Received Signal Strength Indicator (RSSI) measurements from Wi-Fi probe requests is a promising approach. Probe requests are spontaneously emitted by Wi-Fi-enabled devices, are readily captured by of-the-shelf components, and offer the potential for anonymous RSSI measurement. Given the ubiquity of Wi-Fi-enabled devices carried by pedestrians (e.g., smartphones), RSSI-based passive localization in outdoor environments holds promise for mobility monitoring at scale. To this end, we developed the Mobility Intelligence System (MobIntel), comprising inexpensive sensor hardware to collect RSSI data, a cloud backend for data collection and storage, and web-based visualization tools. The system is deployed along Clematis Street in the heart of downtown West Palm Beach, FL, and over the past three years, over 50 sensors have been installed. Our research first confirms that RSSI-based passive localization is feasible in a controlled outdoor environment (i.e., no obstructions and little signal interference), achieving ≤ 4 m localization error in more than 90% of the cases. When significant time-varying signal fluctuations are introduced as a result of long-term deployment, performance can be maintained with an overhaul of the problem formulation and an updated localization model. However, when the outdoor environment is fully uncontrolled (e.g., along Clematis Street), the performance decreases to ≤ 4 m error in fewer than 70% of the cases. However, the drop in performance may be addressed through improved sensor maintenance, additional data collection, and appropriate domain knowledge.
Show less - Date Issued
- 2023
- PURL
- http://purl.flvc.org/fau/fd/FA00014299
- Subject Headings
- Pedestrian traffic flow, Information technology, Computer Science
- Format
- Document (PDF)
- Title
- DEVELOPMENT OF AN AUTOMATED DEVICE FOR THE OPTIMIZED REGULATION OF CEREBROSPINAL FLUID (CSF).
- Creator
- Anjum, Muhammad Waleed, Asghar, Waseem, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Cerebrospinal fluid (CSF) has a role, in keeping the brain and spinal cord safe and nourished within the nervous system (CNS). This clear and colorless fluid is produced in the ventricles of the brain. Surrounds these structures acting as a protective cushion. CSF plays a role in maintaining nervous system health and ensuring optimal functioning. CSF accomplishes four objectives. Protection: The brain and spinal cord are shielded from harm due to CSFs natural shock absorbing properties. This...
Show moreCerebrospinal fluid (CSF) has a role, in keeping the brain and spinal cord safe and nourished within the nervous system (CNS). This clear and colorless fluid is produced in the ventricles of the brain. Surrounds these structures acting as a protective cushion. CSF plays a role in maintaining nervous system health and ensuring optimal functioning. CSF accomplishes four objectives. Protection: The brain and spinal cord are shielded from harm due to CSFs natural shock absorbing properties. This effectively safeguards these structures, from injuries caused by impacts or collisions. Nutrition It ensures a favorable environment for neural cells to perform at their peak by supplying essential nutrients and removing waste products from the brain and spinal cord.
Show less - Date Issued
- 2023
- PURL
- http://purl.flvc.org/fau/fd/FA00014342
- Subject Headings
- Cerebrospinal fluid, Biomedical devices, Biomedical engineering
- Format
- Document (PDF)