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- Title
- Design and implementation of efficient routing protocols in delay tolerant networks.
- Creator
- Liu, Cong., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Delay tolerant networks (DTNs) are occasionally-connected networks that may suffer from frequent partitions. DTNs provide service despite long end to end delays or infrequent connectivity. One fundamental problem in DTNs is routing messages from their source to their destination. DTNs differ from the Internet in that disconnections are the norm instead of the exception. Representative DTNs include sensor-based networks using scheduled intermittent connectivity, terrestrial wireless networks...
Show moreDelay tolerant networks (DTNs) are occasionally-connected networks that may suffer from frequent partitions. DTNs provide service despite long end to end delays or infrequent connectivity. One fundamental problem in DTNs is routing messages from their source to their destination. DTNs differ from the Internet in that disconnections are the norm instead of the exception. Representative DTNs include sensor-based networks using scheduled intermittent connectivity, terrestrial wireless networks that cannot ordinarily maintain end-to-end connectivity, satellite networks with moderate delays and periodic connectivity, underwater acoustic networks with moderate delays and frequent interruptions due to environmental factors, and vehicular networks with cyclic but nondeterministic connectivity. The focus of this dissertation is on routing protocols that send messages in DTNs. When no connected path exists between the source and the destination of the message, other nodes may relay the message to the destination. This dissertation covers routing protocols in DTNs with both deterministic and non-deterministic mobility respectively. In DTNs with deterministic and cyclic mobility, we proposed the first routing protocol that is both scalable and delivery guaranteed. In DTNs with non-deterministic mobility, numerous heuristic protocols are proposed to improve the routing performance. However, none of those can provide a theoretical optimization on a particular performance measurement. In this dissertation, two routing protocols for non-deterministic DTNs are proposed, which minimizes delay and maximizes delivery rate on different scenarios respectively. First, in DTNs with non-deterministic and cyclic mobility, an optimal single-copy forwarding protocol which minimizes delay is proposed., In DTNs with non-deterministic mobility, an optimal multi-copy forwarding protocol is proposed. which maximizes delivery rate under the constraint that the number of copies per message is fixed . Simulation evaluations using both real and synthetic trace are conducted to compare the proposed protocols with the existing ones.
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/210522
- Subject Headings
- Computer network protocols, Computer networks, Reliability, Computer algorithms, Wireless communication systems, Technological innovations
- Format
- Document (PDF)
- Title
- Detection and classification of marine mammal sounds.
- Creator
- Esfahanian, Mahdi, Zhuang, Hanqi, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Ocean is home to a large population of marine mammals such as dolphins and whales and concerns over anthropogenic activities in the regions close to their habitants have been increased. Therefore the ability to detect the presence of these species in the field, to analyze and classify their vocalization patterns for signs of distress and distortion of their communication calls will prove to be invaluable in protecting these species. The objective of this research is to investigate methods...
Show moreOcean is home to a large population of marine mammals such as dolphins and whales and concerns over anthropogenic activities in the regions close to their habitants have been increased. Therefore the ability to detect the presence of these species in the field, to analyze and classify their vocalization patterns for signs of distress and distortion of their communication calls will prove to be invaluable in protecting these species. The objective of this research is to investigate methods that automatically detect and classify vocalization patterns of marine mammals. The first work performed is the classification of bottlenose dolphin calls by type. The extraction of salient and distinguishing features from recordings is a major part of this endeavor. To this end, two strategies are evaluated with real datasets provided by Woods Hole Oceanographic Institution: The first strategy is to use contour-based features such as Time-Frequency Parameters and Fourier Descriptors and the second is to employ texture-based features such as Local Binary Patterns (LBP) and Gabor Wavelets. Once dolphin whistle features are extracted for spectrograms, selection of classification procedures is crucial to the success of the process. For this purpose, the performances of classifiers such as K-Nearest Neighbor, Support Vector Machine, and Sparse Representation Classifier (SRC) are assessed thoroughly, together with those of the underlined feature extractors.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004282, http://purl.flvc.org/fau/fd/FA00004282
- Subject Headings
- Acoustic phenomena in nature, Marine mammals -- Effect of noise on, Marine mammals -- Vocalization, Signal processing -- Mathematics, Underwater acoustics, Wavelets (Mathematics)
- Format
- Document (PDF)
- Title
- Compliance Issues In Cloud Computing Systems.
- Creator
- Yimam, Dereje, Fernandez, Eduardo B., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Appealing features of cloud services such as elasticity, scalability, universal access, low entry cost, and flexible billing motivate consumers to migrate their core businesses into the cloud. However, there are challenges about security, privacy, and compliance. Building compliant systems is difficult because of the complex nature of regulations and cloud systems. In addition, the lack of complete, precise, vendor neutral, and platform independent software architectures makes compliance even...
Show moreAppealing features of cloud services such as elasticity, scalability, universal access, low entry cost, and flexible billing motivate consumers to migrate their core businesses into the cloud. However, there are challenges about security, privacy, and compliance. Building compliant systems is difficult because of the complex nature of regulations and cloud systems. In addition, the lack of complete, precise, vendor neutral, and platform independent software architectures makes compliance even harder. We have attempted to make regulations clearer and more precise with patterns and reference architectures (RAs). We have analyzed regulation policies, identified overlaps, and abstracted them as patterns to build compliant RAs. RAs should be complete, precise, abstract, vendor neutral, platform independent, and with no implementation details; however, their levels of detail and abstraction are still debatable and there is no commonly accepted definition about what an RA should contain. Existing approaches to build RAs lack structured templates and systematic procedures. In addition, most approaches do not take full advantage of patterns and best practices that promote architectural quality. We have developed a five-step approach by analyzing features from available approaches but refined and combined them in a new way. We consider an RA as a big compound pattern that can improve the quality of the concrete architectures derived from it and from which we can derive more specialized RAs for cloud systems. We have built an RA for HIPAA, a compliance RA (CRA), and a specialized compliance and security RA (CSRA) for cloud systems. These RAs take advantage of patterns and best practices that promote software quality. We evaluated the architecture by creating profiles. The proposed approach can be used to build RAs from scratch or to build new RAs by abstracting real RAs for a given context. We have also described an RA itself as a compound pattern by using a modified POSA template. Finally, we have built a concrete deployment and availability architecture derived from CSRA that can be used as a foundation to build compliance systems in the cloud.
Show less - Date Issued
- 2015
- PURL
- http://purl.flvc.org/fau/fd/FA00004559, http://purl.flvc.org/fau/fd/FA00004559
- Subject Headings
- Biometric identification, Client/server computing -- Security measures, Cloud computing -- Security measures, Computational intelligence, Computer software -- Quality control, Electronic information resources -- Access control
- Format
- Document (PDF)
- Title
- Discovery and visualization of co-regulated genes relevant to target diseases.
- Creator
- Lad, Vaibhan., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
In this thesis, we propose to discover co-regulated genes using microarray expression data, as well as providing visualization functionalities for domain experts to study relationships among discovered co-regulated genes. To discover co-regulated genes, we first use existing gene selection methods to select a small portion of genes which are relevant to the target diseases, on which we build an ordered similarity matrix by using nearest neighbor based similarity assessment criteria. We then...
Show moreIn this thesis, we propose to discover co-regulated genes using microarray expression data, as well as providing visualization functionalities for domain experts to study relationships among discovered co-regulated genes. To discover co-regulated genes, we first use existing gene selection methods to select a small portion of genes which are relevant to the target diseases, on which we build an ordered similarity matrix by using nearest neighbor based similarity assessment criteria. We then apply a threshold based clustering algorithm named Spectral Clustering to the matrix to obtain a number of clusters. The genes which are clustered together in one cluster represent a group of co-regulated genes and to visualize them, we use Java Swings as the tool and develop a visualization platform which provides functionalities for domain experts to study relationships between different groups of co-regulated genes; study internal structures within each group of genes, and investigate details of each individual gene and of course for gene function prediction. Results are analyzed based on microarray expression datasets collected from brain tumor, lung cancers and leukemia samples.
Show less - Date Issued
- 2010
- PURL
- http://purl.flvc.org/FAU/2976447
- Subject Headings
- Genomics, Gene mapping, Cell transformation, Cellular signal transduction
- Format
- Document (PDF)
- Title
- Effcient Implementation and Computational Analysis of Privacy-Preserving Protocols for Securing the Financial Markets.
- Creator
- Alvarez, Ramiro, Nojoumian, Mehrdad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Auctions are a key economic mechanism for establishing the value of goods that have an uncertain price. In recent years, as a consequence of the ubiquitous emergence of technology, auctions can reach consumers, and as a result drive market prices, on a global scale. Collection of private information such as past trades exposes more information than desired by market participants. The leaked information can be statistically analyzed to provide auctioneers, or competitors, an advantage on...
Show moreAuctions are a key economic mechanism for establishing the value of goods that have an uncertain price. In recent years, as a consequence of the ubiquitous emergence of technology, auctions can reach consumers, and as a result drive market prices, on a global scale. Collection of private information such as past trades exposes more information than desired by market participants. The leaked information can be statistically analyzed to provide auctioneers, or competitors, an advantage on future transactions. The need to preserve privacy has become a critical concern to reach an accepted level of fairness, and to provide market participants an environment in which they can bid a true valuation. This research is about possible mechanisms to carry out sealed-bid auctions in a distributed setting, and provides the reader with the challenges that currently persevere in the field. The first chapter offers an introduction to different kinds of auction, and to describe sealed-bid auction. The next chapter surveys the literature, and provides necessary theoretical background. Moving on to chapter 3, instead of solely focusing on theoretical aspects of sealed-bid auctions, this chapter dives into implementation details, and demonstrates through communication and computational analysis how different settings affect performance.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013051
- Subject Headings
- Auctions., Financial markets., Tender offers (Securities).
- Format
- Document (PDF)
- Title
- Generalized Feature Embedding Learning for Clustering and Classication.
- Creator
- Golinko, Eric David, Zhu, Xingquan, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Data comes in many di erent shapes and sizes. In real life applications it is common that data we are studying has features that are of varied data types. This may include, numerical, categorical, and text. In order to be able to model this data with machine learning algorithms, it is required that the data is typically in numeric form. Therefore, for data that is not originally numerical, it must be transformed to be able to be used as input into these algorithms. Along with this...
Show moreData comes in many di erent shapes and sizes. In real life applications it is common that data we are studying has features that are of varied data types. This may include, numerical, categorical, and text. In order to be able to model this data with machine learning algorithms, it is required that the data is typically in numeric form. Therefore, for data that is not originally numerical, it must be transformed to be able to be used as input into these algorithms. Along with this transformation it is common that data we study has many features relative to the number of samples in the data. It is often desirable to reduce the number of features that are being trained in a model to eliminate noise and reduce time in training. This problem of high dimensionality can be approached through feature selection, feature extraction, or feature embedding. Feature selection seeks to identify the most essential variables in a dataset that will lead to a parsimonious model and high performing results, while feature extraction and embedding are techniques that utilize a mathematical transformation of the data into a represented space. As a byproduct of using a new representation, we are able to reduce the dimension greatly without sacri cing performance. Oftentimes, by using embedded features we observe a gain in performance. Though extraction and embedding methods may be powerful for isolated machine learning problems, they do not always generalize well. Therefore, we are motivated to illustrate a methodology that can be applied to any data type with little pre-processing. The methods we develop can be applied in unsupervised, supervised, incremental, and deep learning contexts. Using 28 benchmark datasets as examples which include di erent data types, we construct a framework that can be applied for general machine learning tasks. The techniques we develop contribute to the eld of dimension reduction and feature embedding. Using this framework, we make additional contributions to eigendecomposition by creating an objective matrix that includes three main vital components. The rst being a class partitioned row and feature product representation of one-hot encoded data. Secondarily, the derivation of a weighted adjacency matrix based on class label relationships. Finally, by the inner product of these aforementioned values, we are able to condition the one-hot encoded data generated from the original data prior to eigenvector decomposition. The use of class partitioning and adjacency enable subsequent projections of the data to be trained more e ectively when compared side-to-side to baseline algorithm performance. Along with this improved performance, we can adjust the dimension of the subsequent data arbitrarily. In addition, we also show how these dense vectors may be used in applications to order the features of generic data for deep learning. In this dissertation, we examine a general approach to dimension reduction and feature embedding that utilizes a class partitioned row and feature representation, a weighted approach to instance similarity, and an adjacency representation. This general approach has application to unsupervised, supervised, online, and deep learning. In our experiments of 28 benchmark datasets, we show signi cant performance gains in clustering, classi cation, and training time.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013063
- Subject Headings
- Eigenvectors--Data processing., Algorithms., Cluster analysis.
- Format
- Document (PDF)
- Title
- Gene selection for sample sets with biased distribution.
- Creator
- Kamal, Abu Hena Mustafa., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Microarray expression data which contains the expression levels of a large number of simultaneously observed genes have been used in many scientific research and clinical studies. Due to its high dimensionalities, selecting a small number of genes has shown to be beneficial for many tasks such as building prediction models from the microarray expression data or gene regulatory network discovery. Traditional gene selection methods, however, fail to take the class distribution into the...
Show moreMicroarray expression data which contains the expression levels of a large number of simultaneously observed genes have been used in many scientific research and clinical studies. Due to its high dimensionalities, selecting a small number of genes has shown to be beneficial for many tasks such as building prediction models from the microarray expression data or gene regulatory network discovery. Traditional gene selection methods, however, fail to take the class distribution into the selection process. In biomedical science, it is very common to have microarray expression data which is severely biased with one class of examples (e.g., diseased samples) significantly less than other classes (e.g., normal samples). These sample sets with biased distributions require special attention from researchers for identification of genes responsible for a particular disease. In this thesis, we propose three filtering techniques, Higher Weight ReliefF, ReliefF with Differential Minority Repeat and ReliefF with Balanced Minority Repeat to identify genes responsible for fatal diseases from biased microarray expression data. Our solutions are evaluated on five well-known microarray datasets, Colon, Central Nervous System, DLBCL Tumor, Lymphoma and ECML Pancreas. Experimental comparisons with the traditional ReliefF filtering method demonstrate the effectiveness of the proposed methods in selecting informative genes from microarray expression data with biased sample distributions.
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/186330
- Subject Headings
- Gene expression, Research, Methodology, Medical informatics, Apoptosis, Molecular aspects, DNA microarrays, Research
- Format
- Document (PDF)
- Title
- Generating narratives: a pattern language.
- Creator
- Greene, Samuel., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
In order to facilitate the development, discussion, and advancement of the relatively new subfield of Artificial Intelligence focused on generating narrative content, the author has developed a pattern language for generating narratives, along with a new categorization framework for narrative generation systems. An emphasis and focus is placed on generating the Fabula of the story (the ordered sequence of events that make up the plot). Approaches to narrative generation are classified into...
Show moreIn order to facilitate the development, discussion, and advancement of the relatively new subfield of Artificial Intelligence focused on generating narrative content, the author has developed a pattern language for generating narratives, along with a new categorization framework for narrative generation systems. An emphasis and focus is placed on generating the Fabula of the story (the ordered sequence of events that make up the plot). Approaches to narrative generation are classified into one of three categories, and a pattern is presented for each approach. Enhancement patterns that can be used in conjunction with one of the core patterns are also identified. In total, nine patterns are identified - three core narratology patterns, four Fabula patterns, and two extension patterns. These patterns will be very useful to software architects designing a new generation of narrative generation systems.
Show less - Date Issued
- 2012
- PURL
- http://purl.flvc.org/FAU/3355559
- Subject Headings
- Computational intelligence, Pattern recognition systems, Computer vision, Artificial intelligence, Image processing, Digital techiques
- Format
- Document (PDF)
- Title
- HEVC optimization in mobile environments.
- Creator
- Garcia, Ray, Kalva, Hari, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Recently, multimedia applications and their use have grown dramatically in popularity in strong part due to mobile device adoption by the consumer market. Applications, such as video conferencing, have gained popularity. These applications and others have a strong video component that uses the mobile device’s resources. These resources include processing time, network bandwidth, memory use, and battery life. The goal is to reduce the need of these resources by reducing the complexity of the...
Show moreRecently, multimedia applications and their use have grown dramatically in popularity in strong part due to mobile device adoption by the consumer market. Applications, such as video conferencing, have gained popularity. These applications and others have a strong video component that uses the mobile device’s resources. These resources include processing time, network bandwidth, memory use, and battery life. The goal is to reduce the need of these resources by reducing the complexity of the coding process. Mobile devices offer unique characteristics that can be exploited for optimizing video codecs. The combination of small display size, video resolution, and human vision factors, such as acuity, allow encoder optimizations that will not (or minimally) impact subjective quality. The focus of this dissertation is optimizing video services in mobile environments. Industry has begun migrating from H.264 video coding to a more resource intensive but compression efficient High Efficiency Video Coding (HEVC). However, there has been no proper evaluation and optimization of HEVC for mobile environments. Subjective quality evaluations were performed to assess relative quality between H.264 and HEVC. This will allow for better use of device resources and migration to new codecs where it is most useful. Complexity of HEVC is a significant barrier to adoption on mobile devices and complexity reduction methods are necessary. Optimal use of encoding options is needed to maximize quality and compression while minimizing encoding time. Methods for optimizing coding mode selection for HEVC were developed. Complexity of HEVC encoding can be further reduced by exploiting the mismatch between the resolution of the video, resolution of the mobile display, and the ability of the human eyes to acquire and process video under these conditions. The perceptual optimizations developed in this dissertation use the properties of spatial (visual acuity) and temporal information processing (motion perception) to reduce the complexity of HEVC encoding. A unique feature of the proposed methods is that they reduce encoding complexity and encoding time. The proposed HEVC encoder optimization methods reduced encoding time by 21.7% and bitrate by 13.4% with insignificant impact on subjective quality evaluations. These methods can easily be implemented today within HEVC.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004112
- Subject Headings
- Coding theory, Digital coding -- Data processing, Image processing -- Digital techniques, Multimedia systems, Video compression
- Format
- Document (PDF)
- Title
- Exploring the electromagnetics of millimeter-wave through terahertz spectrum: de novo studies vis-à-vis materials science, biomedical applications and wireless communication.
- Creator
- Sharma, Bharti, Neelakanta, Perambur S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The present research is a targeted endeavor to study the underlying characteristics and novel applications of millimeter (mm) wave through terahertz (THz) spectrum of electromagnetic (EM) energy. Focused thereof are the following specific tasks broadly considered pertinent to the said EM spectral range: (i) To elucidate the material characteristics vis-à-vis the interaction with EM energy at the test frequencies; (ii) to identify biomedical applications based on the material characteristics...
Show moreThe present research is a targeted endeavor to study the underlying characteristics and novel applications of millimeter (mm) wave through terahertz (THz) spectrum of electromagnetic (EM) energy. Focused thereof are the following specific tasks broadly considered pertinent to the said EM spectral range: (i) To elucidate the material characteristics vis-à-vis the interaction with EM energy at the test frequencies; (ii) to identify biomedical applications based on the material characteristics studied and applied to biomedia; and (iii) to model the wireless communication channels supporting EM waves at the test frequency bands of interest. Commensurate with the scope as above, the objectives of the research are as follows:
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004330, http://purl.flvc.org/fau/fd/FA00004330
- Subject Headings
- Electromagnetic waves -- Scattering, Pattern recognition systems, Scattering (Physics), Terahertz technology, Wireless communication systems
- Format
- Document (PDF)
- 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
- 2D/3D face recognition.
- Creator
- Guan, Xin., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This dissertation introduces our work on face recognition using a novel approach based on creating 3D face model from 2D face images. Together with the pose angle estimation and illumination compensation, this method can be used successfully to recognize 2D faces with 3D recognition algorithms. The results reported here were obtained partially with our own face image database, which had 2D and 3D face images of 50 subjects, with 9 different pose angles. It is shown that by applying even the...
Show moreThis dissertation introduces our work on face recognition using a novel approach based on creating 3D face model from 2D face images. Together with the pose angle estimation and illumination compensation, this method can be used successfully to recognize 2D faces with 3D recognition algorithms. The results reported here were obtained partially with our own face image database, which had 2D and 3D face images of 50 subjects, with 9 different pose angles. It is shown that by applying even the simple PCA algorithm, this new approach can yield successful recognition rates using 2D probing images and 3D gallery images. The insight gained from the 2D/3D face recognition study was also extended to the case of involving 2D probing and 2D gallery images, which offers a more flexible approach since it is much easier and practical to acquire 2D photos for recognition. To test the effectiveness of the proposed approach, the public AT&T face database, which had 2D only face photos of 40 subjects, with 10 different images each, was utilized in the experimental study. The results from this investigation show that with our approach, the 3D recognition algorithm can be successfully applied to 2D only images. The performance of the proposed approach was further compared with some of the existing face recognition techniques. Studies on imperfect conditions such as domain and pose/illumination variations were also carried out. Additionally, the performance of the algorithms on noisy photos was evaluated. Pros and cons of the proposed face recognition technique along with suggestions for future studies are also given in the dissertation.
Show less - Date Issued
- 2012
- PURL
- http://purl.flvc.org/FAU/3342104
- Subject Headings
- Pattern recognition systems, Optical pattern recognition, Biometric identification, Face perception, Artificial intellingence
- Format
- Document (PDF)
- Title
- A Decision Support System for Sprint Planning in Scrum Practice.
- Creator
- Alhazmi, Alhejab Shawqi, Huang, Shihong, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Scrum is one of the Agile software development processes broadly adopted in industry. Scrum promotes frequent customer involvements and incremental short release. Sprint planning is a critical step in Scrum that sets up next release goals and lays out plans to achieve those goals. This thesis presents a Sprint Planning dEcision Support System (SPESS) which is a tool to assist the managers for Sprint planning. Among considering other Sprint planning factors, SPESS takes into consideration...
Show moreScrum is one of the Agile software development processes broadly adopted in industry. Scrum promotes frequent customer involvements and incremental short release. Sprint planning is a critical step in Scrum that sets up next release goals and lays out plans to achieve those goals. This thesis presents a Sprint Planning dEcision Support System (SPESS) which is a tool to assist the managers for Sprint planning. Among considering other Sprint planning factors, SPESS takes into consideration developer competency, developer seniority and task dependency. The results are that the assignments of the tasks of each Sprint to developers guarantee that each team member contributes to their fullest potential, and project planning is optimized for the shortest possible time. Keywords—Scrum, Sprint planning, planning poker, competence, task dependence, Hungarian algorithm, Essence.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00005970
- Subject Headings
- Scrum (Computer software development), Project management, Agile software development
- Format
- Document (PDF)
- Title
- The "Stop-It anti-fidgeting device.
- Creator
- Barnard, Scott A., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Fidgeting and otherwise constant movements in individuals can be beneficial in those who suffer from Attention Deficit/Hyperactivity Disorder or Generalized Anxiety Disorder as well as others. However this constant movement can also be a distraction to others as well as protrude an air of no self confidence. It is the drawbacks from these actions that we wish to address. By developing an intelligent system that can detect these motions and alert the user, it will allow the wearer of the...
Show moreFidgeting and otherwise constant movements in individuals can be beneficial in those who suffer from Attention Deficit/Hyperactivity Disorder or Generalized Anxiety Disorder as well as others. However this constant movement can also be a distraction to others as well as protrude an air of no self confidence. It is the drawbacks from these actions that we wish to address. By developing an intelligent system that can detect these motions and alert the user, it will allow the wearer of the device to self correct. It is in this self control that one may exhibit more confidence or simply reduce the level of irritation experienced by those in the immediate vicinity. We have designed and built a low cost, mobile, lightweight, untethered, wearable prototype device. It will detect these actions and deliver user selectable biofeedback through a light emitting diode, buzzer, vibromotor or an electric shock to allow for self control.
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/368612
- Subject Headings
- Restless legs syndrome, Treatment, Technological innovations, Agitation (Psychology), Biomedical engineering, Neural networks (Neurobiology)
- Format
- Document (PDF)
- Title
- A Collision-Free Drone Scheduling System.
- Creator
- Steinberg, Andrew, Cardei, Mihaela, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Today, drones have been receiving a lot of notice from commercial businesses. Businesses (mainly companies that have delivery services) are trying to expand their productivity in order bring more satisfaction for their loyal customers. One-way companies can expand their delivery services are through the use of delivery drones. Drones are very powerful devices that are going through many evolutionary changes for their uses throughout the years. For many years, researchers in academia have been...
Show moreToday, drones have been receiving a lot of notice from commercial businesses. Businesses (mainly companies that have delivery services) are trying to expand their productivity in order bring more satisfaction for their loyal customers. One-way companies can expand their delivery services are through the use of delivery drones. Drones are very powerful devices that are going through many evolutionary changes for their uses throughout the years. For many years, researchers in academia have been examining how drones can plan their paths along with avoiding collisions of other drones and certain obstacles in the civil airspace. However, researchers have not considered how the motion path planning can a ect the overall scheduling aspect of civilian drones. In this thesis, we propose an algorithm for a collision-free scheduling motion path planning of a set drones such that they avoid certain obstacles as well as maintaining a safety distance from each other.
Show less - Date Issued
- 2017
- PURL
- http://purl.flvc.org/fau/fd/FA00004994, http://purl.flvc.org/fau/fd/FA00004984
- Subject Headings
- Dissertations, Academic -- Florida Atlantic University, Drone aircraft., Algorithms., Scheduling., Drone aircraft--Safety measures.
- Format
- Document (PDF)
- Title
- Adaptive energy-aware real-time detection models for cardiac atrial fibrillation.
- Creator
- Bouhenguel, Redjem., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Though several clinical monitoring ways exist and have been applied to detect cardiac atril fibrillation (A-Fib) and other arrhythmia, these medical interventions and the ensuing clinical treatments are after the fact and costly. Current portable healthcare monitoring systems come in the form of Ambulatory Event Monitors. They are small, battery-operated electrocardiograph devices used to record the heart's rhythm and activity. However, they are not energy-aware ; they are not personalized ;...
Show moreThough several clinical monitoring ways exist and have been applied to detect cardiac atril fibrillation (A-Fib) and other arrhythmia, these medical interventions and the ensuing clinical treatments are after the fact and costly. Current portable healthcare monitoring systems come in the form of Ambulatory Event Monitors. They are small, battery-operated electrocardiograph devices used to record the heart's rhythm and activity. However, they are not energy-aware ; they are not personalized ; they require long battery life, and ultimately fall short on delivering real-time continuous detection of arrhythmia and specifically progressive development of cardiac A-Fib. The focus of this dissertation is the design of a class of adaptive and efficient energy-aware real-time detection models for monitoring, early real-time detection and reporting of progressive development of cardiac A-Fib.... The design promises to have a greater positive public health impact from predicting A-Fib and providing a viable approach to meeting the energy needs of current and future real-time monitoring, detecting and reporting required in wearable computing healthcare applications that are constrained by scarce energy resources.
Show less - Date Issued
- 2012
- PURL
- http://purl.flvc.org/FAU/3358332
- Subject Headings
- Medical informatics, Medicine, Data processing, Imaging systems in medicine, Design and construction, Cardiovascular system, Diseases, Diagnosis, Bioinformatics
- Format
- Document (PDF)
- Title
- Adaptive Routing Protocols for VANET.
- Creator
- Skiles, Joanne, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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A Vehicular Ad-hoc Network (VANET) is a wireless ad-hoc network that provides communications among vehicles with on-board units and between vehicles and nearby roadside units. The success of a VANET relies on the ability of a routing protocol to ful ll the throughput and delivery requirements of any applications operating on the network. Currently, most of the proposed VANET routing protocols focus on urban or highway environments. This dissertation addresses the need for an adaptive routing...
Show moreA Vehicular Ad-hoc Network (VANET) is a wireless ad-hoc network that provides communications among vehicles with on-board units and between vehicles and nearby roadside units. The success of a VANET relies on the ability of a routing protocol to ful ll the throughput and delivery requirements of any applications operating on the network. Currently, most of the proposed VANET routing protocols focus on urban or highway environments. This dissertation addresses the need for an adaptive routing protocol in VANETs which is able to tolerate low and high-density network tra c with little throughput and delay variation. This dissertation proposes three Geographic Ad-hoc On-Demand Distance Vector (GEOADV) protocols. These three GEOADV routing protocols are designed to address the lack of exibility and adaptability in current VANET routing protocols. The rst protocol, GEOADV, is a hybrid geographic routing protocol. The second protocol, GEOADV-P, enhances GEOADV by introducing predictive features. The third protocol, GEOADV-PF improves optimal route selection by utilizing fuzzy logic in addition to GEOADV-P's predictive capabilities. To prove that GEOADV and GEOADV-P are adaptive their performance is demonstrated by both urban and highway simulations. When compared to existing routing protocols, GEOADV and GEOADV-P lead to less average delay and a higher average delivery ratio in various scenarios. These advantages allow GEOADV- P to outperform other routing protocols in low-density networks and prove itself to be an adaptive routing protocol in a VANET environment. GEOADV-PF is introduced to improve GEOADV and GEOADV-P performance in sparser networks. The introduction of fuzzy systems can help with the intrinsic demands for exibility and adaptability necessary for VANETs. An investigation into the impact adaptive beaconing has on the GEOADV protocol is conducted. GEOADV enhanced with an adaptive beacon method is compared against GEOADV with three xed beacon rates. Our simulation results show that the adaptive beaconing scheme is able to reduce routing overhead, increase the average delivery ratio, and decrease the average delay.
Show less - Date Issued
- 2017
- PURL
- http://purl.flvc.org/fau/fd/FA00004926, http://purl.flvc.org/fau/fd/FA00004926
- Subject Headings
- Vehicular ad hoc networks (Computer networks)--Design and construction., Routing protocols (Computer network protocols), Wireless sensor networks., Computer algorithms., Mobile computing., Mobile communication systems--Technological innovations., Wireless communication systems--Technological innovations., Intelligent transportation systems--Mathematical models.
- Format
- Document (PDF)
- Title
- Adaptive power control in 802.11 networks.
- Creator
- Dural, Serkan., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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IEEE 802.11 networks successfully satisfy high data demands and are cheaper compared to cellular networks. Modern mobile computers and phones are equipped with 802.11 and are VoIP capable. Current network designs do not dynamically accommodate changes in the usage. We propose a dynamic power control algorithm that provides greater capacity within a limited geographic region. Most other power algorithms necessitate changes in 802.11 requiring hardware changes. Proposed algorithm only requires...
Show moreIEEE 802.11 networks successfully satisfy high data demands and are cheaper compared to cellular networks. Modern mobile computers and phones are equipped with 802.11 and are VoIP capable. Current network designs do not dynamically accommodate changes in the usage. We propose a dynamic power control algorithm that provides greater capacity within a limited geographic region. Most other power algorithms necessitate changes in 802.11 requiring hardware changes. Proposed algorithm only requires firmware updates to enable dynamic control of APs transmit power. We use earlier studies to determine the limit of the number of users to optimize power. By lowering transmit power of APs with large number of users, we can effectively decrease the cell size. The resulting gap is then covered by dynamically activating additional APs. This also provides greater flexibility and reduces the network planning costs.
Show less - Date Issued
- 2009
- PURL
- http://purl.flvc.org/FAU/221941
- Subject Headings
- IEEE 802.11 (Standard), Computer networks, Security measures, Computer network protocols, Mobile communication systems, Power supply
- Format
- Document (PDF)
- Title
- Activity analysis and detection of falling and repetitive motion.
- Creator
- Carryl, Clyde, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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This thesis examines the use of motion detection and analysis systems to detect falls and repetitive motion patterns of at-risk individuals. Three classes of motion are examined: Activities of daily living (ADL), falls, and repetitive motion. This research exposes a simple relationship between ADL and non-ADL movement, and shows how to use Principal Component Analysis and a kNN classifier to tell the 2 classes of motion apart with 100% sensitivity and specificity. It also identifies a more...
Show moreThis thesis examines the use of motion detection and analysis systems to detect falls and repetitive motion patterns of at-risk individuals. Three classes of motion are examined: Activities of daily living (ADL), falls, and repetitive motion. This research exposes a simple relationship between ADL and non-ADL movement, and shows how to use Principal Component Analysis and a kNN classifier to tell the 2 classes of motion apart with 100% sensitivity and specificity. It also identifies a more complex relationship between falls and repetitive motion, which both produce bodily accelerations exceeding 3G but differ with regard to their periodicity. This simplifies the classification problem of falls versus repetitive motion when taking into account that their data representations are similar except that repetitive motion displays a high degree of periodicity as compared to falls.
Show less - Date Issued
- 2013
- PURL
- http://purl.flvc.org/FAU/3360774
- Subject Headings
- Perpetual-motion processes, Human locomotion, Neural networks (Computer science), Artificial intelligence
- 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
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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)
