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Physical Sciences and Mathematics Commons™
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- Keyword
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- Data mining (3)
- Support vector machine (3)
- Wireless sensor networks (3)
- Classifier (2)
- Laryngectomy (2)
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- Adaptive Task Partitioning; Thermal-Constrained Task Partitioning; Energy Minimization; Heterogeneous Multi- Core Multiprocessor Real-Time Systems (1)
- Application aware (1)
- Atmospheric Attenuation (1)
- Big Data protection (1)
- Biogeography (1)
- Cellular (1)
- Cellular sensor networks (1)
- Chunk index (1)
- Cloud backup (1)
- Cloud computing (1)
- Cluster deduplication (1)
- Cognitive radio (1)
- Comprehensive two-dimensional gas chromatography (GC × GC) (1)
- Comprehensive two-dimensional liquid chromatography (LC × LC) (1)
- Computational combinatorics (1)
- Computational complexity (1)
- Computer-supported collaborative work (1)
- Configuration management (1)
- Constraint-based processing (1)
- Cross-sample analysis (1)
- Data restructuring (1)
- Data routing (1)
- Database (1)
- Decision tree (1)
- Deduplication (1)
- Publication
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- Department of Computer Science and Engineering: Dissertations, Theses, and Student Research (15)
- CSE Conference and Workshop Papers (14)
- School of Computing: Faculty Publications (5)
- CSE Technical Reports (2)
- Department of Special Education and Communication Disorders: Faculty Publications (2)
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- Computer and Electronics Engineering: Dissertations, Theses, and Student Research (1)
- Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research (1)
- Department of Mathematics: Dissertations, Theses, and Student Research (1)
- Erforschung biologischer Ressourcen der Mongolei / Exploration into the Biological Resources of Mongolia, ISSN 0440-1298 (1)
Articles 1 - 30 of 42
Full-Text Articles in Physical Sciences and Mathematics
Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi
Data Mining Of Pancreatic Cancer Protein Databases, Peter Revesz, Christopher Assi
CSE Conference and Workshop Papers
Data mining of protein databases poses special challenges because many protein databases are non- relational whereas most data mining and machine learning algorithms assume the input data to be a type of rela- tional database that is also representable as an ARFF file. We developed a method to restructure protein databases so that they become amenable for various data mining and machine learning tools. Our restructuring method en- abled us to apply both decision tree and support vector machine classifiers to a pancreatic protein database. The SVM classifier that used both GO term and PFAM families to characterize proteins gave …
Identification Of Tcp Protocols, Juan Shao
Identification Of Tcp Protocols, Juan Shao
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Recently, many new TCP algorithms, such as BIC, CUBIC, and CTCP, have been deployed in the Internet. Investigating the deployment statistics of these TCP algorithms is meaningful to study the performance and stability of the Internet. Currently, there is a tool named Congestion Avoidance Algorithm Identification (CAAI) for identifying the TCP algorithm of a web server and then for investigating the TCP deployment statistics. However, CAAI using a simple k-NN algorithm can not achieve a high identification accuracy. In this thesis, we comprehensively study the identification accuracy of five popular machine learning models. We find that the random forest model …
Dynamic Data Race Detection And Healing, Du Li
Dynamic Data Race Detection And Healing, Du Li
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Perpetual availability is an important operational goal in today's computer systems. However, achieving this goal is challenging because modern software systems contain faults that can cause them to fail. For example, multi-threading is widely used in modern software to fully utilize the computing capability of multicore processors. However, employing multi-threading can lead to concurrency faults such as deadlock and data race that are notoriously difficult to to isolate, detect, and repair.Data races, which involves two concurrent accesses to the same data where at least one is a write, are the most common concurrency faults.
As our first step, we investigate …
Hog: Distributed Hadoop Mapreduce On The Grid, Chen He, Derek J. Weitzel, David Swanson, Ying Lu
Hog: Distributed Hadoop Mapreduce On The Grid, Chen He, Derek J. Weitzel, David Swanson, Ying Lu
CSE Conference and Workshop Papers
MapReduce is a powerful data processing platform for commercial and academic applications. In this paper, we build a novel Hadoop MapReduce framework executed on the Open Science Grid which spans multiple institutions across the United States – Hadoop On the Grid (HOG). It is different from previous MapReduce platforms that run on dedicated environments like clusters or clouds. HOG provides a free, elastic, and dynamic MapReduce environment on the opportunistic resources of the grid. In HOG, we improve Hadoop’s fault tolerance for wide area data analysis by mapping data centers across the U.S. to virtual racks and creating multi-institution failure …
Temporal Data Mining Of Uncertain Water Reservoir Data, Abhinaya Mohan, Peter Revesz
Temporal Data Mining Of Uncertain Water Reservoir Data, Abhinaya Mohan, Peter Revesz
CSE Conference and Workshop Papers
This paper describes the challenges of data mining uncertain water reservoir data based on past human operations in order to learn from them reservoir policies that can be automated for the future operation of the water reservoirs. Records of human operations of water reservoirs often contain uncertain data. For example, the recorded amounts of water released and retained in the water reservoirs are typically uncertain, i.e., they are bounded by some minimum and maximum values. Moreover, the time of release is also uncertain, i.e., typically only monthly or weekly amounts are recorded. To increase the effectiveness of data mining of …
Improving Performance Of Solid State Drives In Enterprise Environment, Jian Hu
Improving Performance Of Solid State Drives In Enterprise Environment, Jian Hu
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Flash memory, in the form of Solid State Drive (SSD), is being increasingly employed in mobile and enterprise-level storage systems due to its superior features such as high energy efficiency, high random read performance and small form factor. However, SSD suffers from the erase-before-write and endurance problems, which limit the direct deployment of SSD in enterprise environment. Existing studies either develop SSD-friendly on-board buffer management algorithms, or design sophisticated Flash Translation Layers (FTL) to ease the erase-before-write problem. This dissertation addresses the two issues and consists of two parts.
The first part focuses on the white-box approaches that optimize the …
Whole-Word Recognition From Articulatory Movements For Silent Speech Interfaces, Jun Wang, Ashok Samal, Jordan R. Green, Frank Rudzicz
Whole-Word Recognition From Articulatory Movements For Silent Speech Interfaces, Jun Wang, Ashok Samal, Jordan R. Green, Frank Rudzicz
Department of Special Education and Communication Disorders: Faculty Publications
Articulation-based silent speech interfaces convert silently produced speech movements into audible words. These systems are still in their experimental stages, but have significant potential for facilitating oral communication in persons with laryngectomy or speech impairments. In this paper, we report the result of a novel, real-time algorithm that recognizes whole-words based on articulatory movements. This approach differs from prior work that has focused primarily on phoneme-level recognition based on articulatory features. On average, our algorithm missed 1.93 words in a sequence of twenty-five words with an average latency of 0.79 seconds for each word prediction using a data set of …
Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson
Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
For over two decades, satellite sensors have provided the locations of global fire activity with ever-increasing accuracy. However, the ability to measure fire intensity, know as fire radiative power (FRP), and its potential relationships to meteorology and smoke plume injection heights, are currently limited by the pixel resolution. This dissertation describes the development of a new, sub-pixel-based FRP calculation (FRPf) for fire pixels detected by the MODerate Resolution Imaging Spectroradiometer (MODIS) fire detection algorithm (Collection 5), which is subsequently applied to several large wildfire events in North America. The methodology inherits an earlier bi-spectral algorithm for retrieving sub-pixel …
Automation Of Landmark Selection For Rodent Brain Mri-Histology Registration Using Thin-Plate Splines, Ayan Sengupta
Automation Of Landmark Selection For Rodent Brain Mri-Histology Registration Using Thin-Plate Splines, Ayan Sengupta
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Image registration is the process of aligning two different images of the same object taken at different times, at different orientations or using different instruments. This is common in medical applications since multiple modalities are used to image different parts of the body. This is an important early step in many diagnostic procedures such as change detection, monitoring tumor or quantifying spread of a disease. The widely used landmark based registration approach is tedious, time consuming, inconsistent and error prone. Furthermore, the standard schemes based on rigid and affine transformation can only describe global geometric differences between the objects of …
Palantir: Early Detection Of Development Conflicts Arising From Parallel Code Changes, Anita Sarma, D F. Redmiles, Andre Van Der Hoek
Palantir: Early Detection Of Development Conflicts Arising From Parallel Code Changes, Anita Sarma, D F. Redmiles, Andre Van Der Hoek
School of Computing: Faculty Publications
The earlier a conflict is detected, the easier it is to resolve—this is the main precept of workspace awareness. Workspace awareness seeks to provide users with information of relevant ongoing parallel changes occurring in private workspaces, thereby enabling the early detection and resolution of potential conflicts. The key approach is to unobtrusively inform developers of potential conflicts arising because of concurrent changes to the same file and dependency violations in ongoing parallel work. This paper describes our research goals, approach, and implementation of workspace awareness through Palantır and includes a comprehensive evaluation involving two laboratory experiments. We present both quantitative …
Routing Over The Interplanetary Internet, Joyeeta Mukherjee
Routing Over The Interplanetary Internet, Joyeeta Mukherjee
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Future space exploration demands a Space Network that will be able to connect spacecrafts with one another and in turn with Earth's terrestrial Internet and hence efficiently transfer data back and forth. The feasibility of this technology would enable common people to directly access telemetric data from distant planets and satellites. The concept of an Interplanetary Internet (IPN) is only in its incubation stage and considerable amount of common standards and research is required before widespread deployment can occur to make IPN feasible.
We provide a comprehensive survey that presents a picture of the current space networking technologies and architectures. …
Simulation, Development And Deployment Of Mobile Wireless Sensor Networks For Migratory Bird Tracking, William P. Bennett Jr
Simulation, Development And Deployment Of Mobile Wireless Sensor Networks For Migratory Bird Tracking, William P. Bennett Jr
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reliable, low-cost monitoring of migratory species. The developed multi-tier architecture yields ecologists with unconventional behavior information not furnished by alternative tracking systems at such a large scale and for a low-cost. The simulation, development and implementation of the CraneTracker software system is presented. The system is shown effective through multiple proxy deployments on wildlife and has been operational for 10 months …
Statistical Software Properties: Definition, Inference And Monitoring, Javier A. Darsie
Statistical Software Properties: Definition, Inference And Monitoring, Javier A. Darsie
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Software properties define how software systems should operate. Specifying correct properties, however, can be difficult and expensive as it requires deep knowledge of the system's expected behavior and the environment in which it operates. Automated analysis techniques to infer properties from code or code executions can mitigate that cost, but are still unable to go beyond state properties and the simplest patterns of temporal properties. This limitation renders properties that sacrifice fault detection power.
To address this problem, we introduce a new type of software properties called \textit{statistical properties}, which characterize significant statistical relationships among the values of variables across …
Data Mining Of Protein Databases, Christopher Assi
Data Mining Of Protein Databases, Christopher Assi
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Data mining of protein databases poses special challenges because many protein databases are non-relational whereas most data mining and machine learning algorithms assume the input data to be a relational database. Protein databases are non-relational mainly because they often contain set data types. We developed new data mining algorithms that can restructure non-relational protein databases so that they become relational and amenable for various data mining and machine learning tools. We applied the new restructuring algorithms to a pancreatic protein database. After the restructuring, we also applied two classification methods, such as decision tree and SVM classifiers and compared their …
A Wlan Fingerprinting Based Indoor Localization Technique, Landu Jiang
A Wlan Fingerprinting Based Indoor Localization Technique, Landu Jiang
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Satellite-based Global Positioning Systems (GPS) have enabled a variety of location-based services such as navigation systems, and become increasingly popular and important in our everyday life. However, GPS does not work well in indoor environments where walls, floors and other construction objects greatly attenuate satellite signals.
In this paper, we propose an Indoor Positioning System (IPS) based on widely deployed indoor WiFi systems. Our system uses not only the Received Signal Strength (RSS) values measured at the current location but also the previous location information to determine the current location of a mobile user. We have conducted a large number …
On Heterogeneous User Demands In Peer-To-Peer Video Streaming Systems, Zhipeng Ouyang
On Heterogeneous User Demands In Peer-To-Peer Video Streaming Systems, Zhipeng Ouyang
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
A Peer-to-Peer (P2P) video streaming system usually consists of a large number of peers, which have heterogeneous physical properties. Orthogonal to the physical heterogeneity, there is another type of heterogeneity called demand heterogeneity. Namely, peers have their own demands on the quality and type of the streaming service. The problem of demand heterogeneity has received little attention and as a result current P2P video streaming systems cannot achieve satisfactory performance due to demand heterogeneity. In this dissertation, we study how to design efficient P2P video streaming systems with heterogeneous user demands.
First, we study the problem of heterogeneous user demands …
Solving The Search For Suitable Code: An Initial Implementation, Kathryn T. Stolee, Sebastian Elbaum
Solving The Search For Suitable Code: An Initial Implementation, Kathryn T. Stolee, Sebastian Elbaum
CSE Technical Reports
Searching for code is a common task among programmers, with the ultimate goal of finding and reusing code or getting ideas for implementation. While the process of searching for code - issuing a query and selecting a relevant match - is straightforward, several costs must be balanced, including the costs of specifying the query, examining the results to find desired code, and not finding a relevant result. For the popular syntactic searches the query cost is quite low, but the results are often vague or irrelevant, so the examination cost is high and matches may not be found. Semantic searches …
A Scalable Inline Cluster Deduplication Framework For Big Data Protection, Yinjin Fu, Hong Jiang, Nong Xiao
A Scalable Inline Cluster Deduplication Framework For Big Data Protection, Yinjin Fu, Hong Jiang, Nong Xiao
CSE Technical Reports
Cluster deduplication has become a widely deployed technology in data protection services for Big Data to satisfy the requirements of service level agreement (SLA). However, it remains a great challenge for cluster deduplica- tion to strike a sensible tradeoff between the conflicting goals of scalable dedu- plication throughput and high duplicate elimination ratio in cluster systems with low-end individual secondary storage nodes. We propose Σ-Dedupe, a scalable inline cluster deduplication framework, as a middleware deployable in cloud da- ta centers, to meet this challenge by exploiting data similarity and locality to op- timize cluster deduplication in inter-node and intra-node scenarios, …
An Enhanced Self-Adaptive Mapreduce Scheduling Algorithm, Xiaoyu Sun
An Enhanced Self-Adaptive Mapreduce Scheduling Algorithm, Xiaoyu Sun
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
MapReduce is a framework for processing huge amounts of data in a distributed environment and Hadoop is Apache’s open source implementation of MapReduce, which is widely used. However, Hadoop’s performance is currently limited by its default task scheduler, which assumes that cluster nodes are homogeneous when estimating the task progress and choosing slow tasks for re-execution. In practice, the homogeneity assumption does not always hold. Longest Approximate Time to End (LATE) is a scheduling algorithm that takes heterogeneity into account. It, however, still depends on a static method to estimate the task execution time. As a result, neither Hadoop default …
Resonant Wireless Power Transfer To Ground Sensors From A Uav, Brent Griffin, Carrick Detweiler
Resonant Wireless Power Transfer To Ground Sensors From A Uav, Brent Griffin, Carrick Detweiler
CSE Conference and Workshop Papers
Wireless magnetic resonant power transfer is an emerging technology that has many advantages over other wireless power transfer methods due to its safety, lack of interference, and efficiency at medium ranges. In this paper, we develop a wireless magnetic resonant power transfer system that enables unmanned aerial vehicles (UAVs) to provide power to, and recharge batteries of wireless sensors and other electronics far removed from the electric grid. We address the difficulties of implementing and outfitting this system on a UAV with limited payload capabilities and develop a controller that maximizes the received power as the UAV moves into and …
A Multi-Modal Sensing And Communication Platform For Continental-Scale Migratory Bird Tracking, David J. Anthony
A Multi-Modal Sensing And Communication Platform For Continental-Scale Migratory Bird Tracking, David J. Anthony
Computer and Electronics Engineering: Dissertations, Theses, and Student Research
This thesis presents a novel platform for tracking migratory birds on a continental scale. Cellular technology is used to augment the short-range radios that have traditionally been used in wireless sensor networks. The platform utilizes multiple sensors, including a GPS and solid state compass. By using these sensors, the platform is capable of not only tracking a bird’s migration path, but also provides information on a bird’s behavior during its life-cycle. Testing methodology utilizing simulations and aspect-oriented programming is used to reveal faults in the platform prior to deployment on wild animals. In collaboration with the International Crane Foundation, and …
Probabilistic Qos Analysis In Wireless Sensor Networks, Yunbo Wang
Probabilistic Qos Analysis In Wireless Sensor Networks, Yunbo Wang
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Emerging applications of wireless sensor networks (WSNs) require real-time quality of service (QoS) guarantees to be provided by the network. Traditional analysis work only focuses on the first-order statistics, such as the mean and the variance of the QoS performance. However, due to unique characteristics of WSNs, a cross-layer probabilistic analysis of QoS performance is essential. In this dissertation, a comprehensive cross-layer probabilistic analysis framework is developed to investigate the probabilistic evaluation and optimization of QoS performance provided by WSNs. In this framework, the distributions of QoS performance metrics are derived, which are natural tools to discover the probabilities to …
Cogtool-Helper: Leveraging Gui Functional Testing Tools To Generate Predictive Human Performance Models, Amanda Swearngin
Cogtool-Helper: Leveraging Gui Functional Testing Tools To Generate Predictive Human Performance Models, Amanda Swearngin
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Numerous tools and techniques for human performance modeling have been introduced in the field of human-computer interaction. With such tools comes the ability to model legacy applications. Models can be used to compare design ideas to existing applications, or to evaluate products against those of competitors. One such mod- eling tool, CogTool, allows user interface designers and analysts to mock up design ideas, demonstrate tasks, and obtain human performance predictions for those tasks. This is one step towards a simple and complete analysis process, but it still requires a large amount of manual work. Graphical user interface (GUI) testing tools …
Supporting Developer-Onboarding With Enhanced Resource Finding And Visual Exploration, Jianguo Wang
Supporting Developer-Onboarding With Enhanced Resource Finding And Visual Exploration, Jianguo Wang
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Understanding the basic structure of a code base and a development team are essential to get new developers up to speed in a software development project. Developers do so through the process of early experimentation with code and the creation of mental models of technical and social structures in a project. However, getting up-to-speed in a new project can be challenging due to difficulties in: finding the right place to begin explorations, expanding the focus to determine relevant resources for tasks, and identifying dependencies across project elements to gain a high-level overview of project structures. In this thesis, I first …
Improving Backup And Restore Performance For Deduplication-Based Cloud Backup Services, Stephen Mkandawire
Improving Backup And Restore Performance For Deduplication-Based Cloud Backup Services, Stephen Mkandawire
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
The benefits provided by cloud computing and the space savings offered by data deduplication make it attractive to host data storage services like backup in the cloud. Data deduplication relies on comparing fingerprints of data chunks, and store them in the chunk index, to identify and remove redundant data, with an ultimate goal of saving storage space and network bandwidth.
However, the chunk index presents a bottleneck to the throughput of the backup operation. While several solutions to address deduplication throughput have been proposed, the chunk index is still a centralized resource and limits the scalability of both storage capacity …
Combinatorics Using Computational Methods, Derrick Stolee
Combinatorics Using Computational Methods, Derrick Stolee
Department of Mathematics: Dissertations, Theses, and Student Research
Computational combinatorics involves combining pure mathematics, algorithms, and computational resources to solve problems in pure combinatorics. This thesis provides a theoretical framework for combinatorial search, which is then applied to several problems in combinatorics. Some results in space-bounded computational complexity are also presented.
Sentence Recognition From Articulatory Movements For Silent Speech Interfaces, Jun Wang, Ashok Samal, Jordan R. Green, Frank Rudzicz
Sentence Recognition From Articulatory Movements For Silent Speech Interfaces, Jun Wang, Ashok Samal, Jordan R. Green, Frank Rudzicz
Department of Special Education and Communication Disorders: Faculty Publications
Recent research has demonstrated the potential of using an articulation-based silent speech interface for command-and-control systems. Such an interface converts articulation to words that can then drive a text-to-speech synthesizer. In this paper, we have proposed a novel near-time algorithm to recognize whole-sentences from continuous tongue and lip movements. Our goal is to assist persons who are aphonic or have a severe motor speech impairment to produce functional speech using their tongue and lips. Our algorithm was tested using a functional sentence data set collected from ten speakers (3012 utterances). The average accuracy was 94.89% with an average latency of …
Cross-Layer Analysis Of The End-To-End Delay Distribution In Wireless Sensor Networks, Yunbo Wang, Mehmet C. Vuran, Steve Goddard
Cross-Layer Analysis Of The End-To-End Delay Distribution In Wireless Sensor Networks, Yunbo Wang, Mehmet C. Vuran, Steve Goddard
School of Computing: Faculty Publications
Emerging applications of wireless sensor networks (WSNs) require real-time quality-of-service (QoS) guarantees to be provided by the network. Due to the nondeterministic impacts of the wireless channel and queuing mechanisms, probabilistic analysis of QoS is essential. One important metric of QoS in WSNs is the probability distribution of the end-to-end delay. Compared to other widely used delay performance metrics such as the mean delay, delay variance, and worst-case delay, the delay distribution can be used to obtain the probability to meet a specific deadline for QoS-based communication in WSNs. To investigate the end-to-end delay distribution, in this paper, a comprehensive …
Adaptive Energy-Efficient Task Partitioning For Heterogeneous Multi-Core Multiprocessor Real-Time Systems, Shivashis Saha, Jitender S. Deogun, Ying Lu
Adaptive Energy-Efficient Task Partitioning For Heterogeneous Multi-Core Multiprocessor Real-Time Systems, Shivashis Saha, Jitender S. Deogun, Ying Lu
CSE Conference and Workshop Papers
The designs of heterogeneous multi-core multiprocessor real-time systems are evolving for higher energy efficiency at the cost of increased heat density. This adversely effects the reliability and performance of the real-time systems. Moreover, the partitioning of periodic real-time tasks based on their worst case execution time can lead to significant energy wastage.
In this paper, we investigate adaptive energy-efficient task partitioning for heterogeneous multi-core multiprocessor realtime systems. We use a power model which incorporates the impact of temperature and voltage of a processor on its static power consumption. Two different thermal models are used to estimate the peak temperature of …
Hyscaleii: A High Performance Hybrid Optical Network Architecture For Data Centers, Shivashis Saha, Jitender S. Deogun, Lisong Xu
Hyscaleii: A High Performance Hybrid Optical Network Architecture For Data Centers, Shivashis Saha, Jitender S. Deogun, Lisong Xu
CSE Conference and Workshop Papers
Tremendous growth in data-intensive cloud applications have resulted in an increased demand for highly scalable data center network (DCN) architectures with high throughput and low network complexity. In this paper, we propose HyScaleII to improve the performance of HyScale [17]. HyScaleII is a switchcentric high performance hybrid optical network based DCN architecture that has most of the desirable properties of a data center, e.g. high scalability, low diameter, high bisection width, fault-tolerance, and low network complexity. We also present an efficient and simple routing scheme called HySII routing, which exploits the structural properties of HyScaleII. In our experiments, HyScaleII …