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Articles 1 - 18 of 18
Full-Text Articles in Physical Sciences and Mathematics
Ensight, Jonathan Hefner
An Empirical Study Of Imputation Techniques For Software Data Sets, Sumanth Yenduri
An Empirical Study Of Imputation Techniques For Software Data Sets, Sumanth Yenduri
LSU Doctoral Dissertations
Software Project Effort/Cost/Time Estimation has been one of the hot topics of research in the current software engineering industry. Solutions for effort/cost/time estimation are in great demand. Knowledge of accurate effort/cost/time estimates early in the software project life cycle enables project managers manage and exploit resources efficiently. The constraints of cost and time can also be met. To this day, most companies rely on their historical database of past project data sets to predict estimates for future projects. Like other data sets, software project data sets also suffer from numerous problems. The most important problem is they contain missing/incomplete data. …
Efficient Automatic Correction And Segmentation Based 3d Visualization Of Magnetic Resonance Images, Mikhail V. Milchenko
Efficient Automatic Correction And Segmentation Based 3d Visualization Of Magnetic Resonance Images, Mikhail V. Milchenko
LSU Doctoral Dissertations
In the recent years, the demand for automated processing techniques for digital medical image volumes has increased substantially. Existing algorithms, however, still often require manual interaction, and newly developed automated techniques are often intended for a narrow segment of processing needs. The goal of this research was to develop algorithms suitable for fast and effective correction and advanced visualization of digital MR image volumes with minimal human operator interaction. This research has resulted in a number of techniques for automated processing of MR image volumes, including a novel MR inhomogeneity correction algorithm derivative surface fitting (dsf), automatic tissue detection algorithm …
Active Security Mechanisms For Wireless Sensor Networks And Energy Optimization For Passive Security Routing, Lydia Ray
LSU Doctoral Dissertations
Wireless sensor networks consisting of numerous tiny low power autonomous sensor nodes provide us with the remarkable ability to remotely view and interact with the previously unobservable physical world. However, incorporating computation intensive security measures in sensor networks with limited resources is a challenging research issue. The objective of our thesis is to explore different security aspects of sensor networks and provide novel solutions for significant problems. We classify security mechanisms into two categories - active category and passive category. The problem of providing a secure communication infrastructure among randomly deployed sensor nodes requires active security measurements. Key pre-distribution is …
Learning Discrete Hidden Markov Models From State Distribution Vectors, Luis G. Moscovich
Learning Discrete Hidden Markov Models From State Distribution Vectors, Luis G. Moscovich
LSU Doctoral Dissertations
Hidden Markov Models (HMMs) are probabilistic models that have been widely applied to a number of fields since their inception in the late 1960’s. Computational Biology, Image Processing, and Signal Processing, are but a few of the application areas of HMMs. In this dissertation, we develop several new efficient learning algorithms for learning HMM parameters. First, we propose a new polynomial-time algorithm for supervised learning of the parameters of a first order HMM from a state probability distribution (SD) oracle. The SD oracle provides the learner with the state distribution vector corresponding to a query string. We prove the correctness …
Energy-Rate Based Mac Protocol For Wireless Sensor Networks And Key Pre-Distribution Schemes, Ramaraju Kalidindi
Energy-Rate Based Mac Protocol For Wireless Sensor Networks And Key Pre-Distribution Schemes, Ramaraju Kalidindi
LSU Master's Theses
Sensor networks are typically unattended because of their deployment in hazardous, hostile or remote environments. This makes the problem of conserving energy at individual sensor nodes challenging. S-MAC and PAMAS are two MAC protocols which periodically put nodes (selected at random) to sleep in order to achieve energy savings. Unlike these protocols, we propose an approach in which node duty cycles (i.e sleep and wake schedules) are based on their criticality. A distributed algorithm is used to find sets of winners and losers, who are then assigned appropriate slots in our TDMA based MAC protocol. We introduce the concept of …
Adaptive Remote Visualization System With Optimized Network Performance For Large Scale Scientific Data, Mengxia Zhu
Adaptive Remote Visualization System With Optimized Network Performance For Large Scale Scientific Data, Mengxia Zhu
LSU Doctoral Dissertations
This dissertation discusses algorithmic and implementation aspects of an automatically configurable remote visualization system, which optimally decomposes and adaptively maps the visualization pipeline to a wide-area network. The first node typically serves as a data server that generates or stores raw data sets and a remote client resides on the last node equipped with a display device ranging from a personal desktop to a powerwall. Intermediate nodes can be located anywhere on the network and often include workstations, clusters, or custom rendering engines. We employ a regression model-based network daemon to estimate the effective bandwidth and minimal delay of a …
Energy Aware Topology Control Protocols For Wireless Sensor Networks, Shilpa Dhar
Energy Aware Topology Control Protocols For Wireless Sensor Networks, Shilpa Dhar
LSU Master's Theses
Wireless Sensor Network has emerged as an important technology of the future due to its potential for application across a wide array of domains. The collaborative power of numerous autonomousremote sensing nodes self configured into a multi hop network permits in-depth accurate observation of any physical phenomenon. A stringent set of computational and resource constraints make the design and implementation of sensor networks an arduous task. The issue of optimizing the limited and often non-renewable energy of sensor nodes due to its direct impact on network lifetime dominates every aspect of wireless sensor networks. Existing techniques for optimizing energy consumption …
Simulation Study For Wireless Sensor Networks And Load Sharing Routing Protocol To Increase Network Life And Connectivity, Ankur Suri
LSU Master's Theses
LSU SensorSimulator is a framework for simulating wireless sensor networks. It is a customizable and extendible simulator, which allows testing and analyzing software for wireless sensor networks. The users can subclass the framework classes and customize the behavior of various network layers. This subclassing gives a way to the developers an opportunity to analyze and investigate, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, independent of hardware constraint. The results are compared against the simulation results for ns-2 for routing protocols Directed Diffusion and GEAR. Through the comparison of results for scalability, performance and memory …
Sensorsimulator: Simulation Framework For Sensor Networks, Cariappa D. Mallanda
Sensorsimulator: Simulation Framework For Sensor Networks, Cariappa D. Mallanda
LSU Master's Theses
Wireless sensor networks have the potential to become significant subsystems of engineering applications. Before relegating important and safety-critical tasks to such subsystems, it is necessary to understand the dynamic behavior of these subsystems in simulation environments. There is an urgent need to develop a simulation platform that is useful to explore both the networking issues and the distributed computing aspects of wireless sensor networks. Current approaches to simulating wireless sensor networks largely focus on the networking issues. These approaches use well-known network simulation tools that are often difficult to extend to explore distributed computing issues. Discrete-event simulation is a trusted …
A Parallel Computing-Visualization Framework For Polycrystalline Minerals, Venkatasrirama Pavankumar Yerraguntla
A Parallel Computing-Visualization Framework For Polycrystalline Minerals, Venkatasrirama Pavankumar Yerraguntla
LSU Master's Theses
In this report, we have reported some preliminary results in the development of a parallel computing-visualization framework for large-scale molecular dynamics simulations of polycrystals of minerals, which are geophysically relevant for Earth’s mantle. First, we have generated the input configurations of atoms belonging to various grains distributed in the space in a way, which resembles the polycrystalline structure of the minerals. The Input configuration is developed using Voronoi geometry. Thus generated polycrystalline system is simulated using the PolyCrystal Molecular Dynamics algorithm. Performance tests conducted using up to 256 processors and a couple of millions of atoms have shown that the …
Visualization Based On Interactive Clipping: Application To Confocal Data, Gaurav Khanduja
Visualization Based On Interactive Clipping: Application To Confocal Data, Gaurav Khanduja
LSU Master's Theses
We have explored how clipping can be exploited in an interactive manner to visualize massive three-dimensional datasets. In essence, the proposed interactive clipping approach involves the dynamic adjustment of the clipping plane to expose any cross-section of the volume data and subsequent adjustment of the clipped surface to the best view position using a combination of rotation and translation. The thesis describes the design, implementation and application of our interactive-clipping-based visualization system. The implementation is done with OpenGL and C++, thus resulting in a highly portable and flexible system. For illustration, two types of scientific datasets, confocal data of a …
Secure 3g User Authentication In Ad-Hoc Serving Networks, Lyn L. Evans
Secure 3g User Authentication In Ad-Hoc Serving Networks, Lyn L. Evans
LSU Master's Theses
The convergence of cellular and IP technologies has pushed the integration of 3G and WLAN networks to the forefront. With 3G networks' failure to deliver feasible bandwidth to the customer and the emerging popularity, ease of use and high throughput of 802.11 WLANs, integrating secure access to 3G services from WLANs has become a primary focus. 3G user authentication initiated from WLANs has been defined by an enhancement to the extensible authentication protocol, EAP, used to transport user authentication requests over WLANs. The EAP-AKA protocol executes the 3G USIM user challenge and response authentication process over the IP backbone for …
Simulation Study Of Routing Protocols In Wireless Sensor Networks, Vatsalya Kunchakarra
Simulation Study Of Routing Protocols In Wireless Sensor Networks, Vatsalya Kunchakarra
LSU Master's Theses
Wireless sensor networks, a distributed network of sensor nodes perform critical tasks in many application areas such as target tracking in military applications, detection of catastrophic events, environment monitoring, health applications etc. The routing protocols developed for these distributed sensor networks need to be energy efficient and scalable. To create a better understanding of the performance of various routing protocols proposed it is very important to perform a detailed analysis of them. Network simulators enable us to study the performance and behavior of these protocols on various network topologies. Many Sensor Network frameworks were developed to explore both the networking …
Automatic Segmentation Of Magnetic Resonance Images Of The Brain, Kirk V. N. Spence
Automatic Segmentation Of Magnetic Resonance Images Of The Brain, Kirk V. N. Spence
LSU Doctoral Dissertations
Magnetic resonance imaging (MRI) is a technique used primarily in medical settings to produce high quality images of the human body’s internal anatomy. Each image is of a thin slice through the body, with the typical distance between slices being a few millimeters. Brain segmentation is the delineation of one or more anatomical structures within images of the brain. It promotes greater understanding of spatial relationships to aid in such tasks as surgical planning and clinical diagnoses, particularly when the segmented outlines from each image slice are displayed together as a surface in three-dimensions. A review of the literature indicates …
Medical Image Enhancement, Alina Monica Trifas
Medical Image Enhancement, Alina Monica Trifas
LSU Doctoral Dissertations
Each image acquired from a medical imaging system is often part of a two-dimensional (2-D) image set whose total presents a three-dimensional (3-D) object for diagnosis. Unfortunately, sometimes these images are of poor quality. These distortions cause an inadequate object-of-interest presentation, which can result in inaccurate image analysis. Blurring is considered a serious problem. Therefore, “deblurring” an image to obtain better quality is an important issue in medical image processing. In our research, the image is initially decomposed. Contrast improvement is achieved by modifying the coefficients obtained from the decomposed image. Small coefficient values represent subtle details and are amplified …
Broadcast In Sparse Conversion Optical Networks Using Fewest Converters, Tong Yi
Broadcast In Sparse Conversion Optical Networks Using Fewest Converters, Tong Yi
LSU Doctoral Dissertations
Wavelengths and converters are shared by communication requests in optical networks. When a message goes through a node without a converter, the outgoing wavelength must be the same as the incoming one. This constraint can be removed if the node uses a converter. Hence, the usage of converters increases the utilization of wavelengths and allows more communication requests to succeed. Since converters are expensive, we consider sparse conversion networks, where only some specified nodes have converters. Moreover, since the usage of converters induces delays, we should minimize the use of available converters. The Converters Usage Problem (CUP) is to use …
Biologically Inspired Learning System, Patrick Mcdowell
Biologically Inspired Learning System, Patrick Mcdowell
LSU Doctoral Dissertations
Learning Systems used on robots require either a-priori knowledge in the form of models, rules of thumb or databases or require that robot to physically execute multitudes of trial solutions. The first requirement limits the robot’s ability to operate in unstructured changing environments, and the second limits the robot’s service life and resources. In this research a generalized approach to learning was developed through a series of algorithms that can be used for construction of behaviors that are able to cope with unstructured environments through adaptation of both internal parameters and system structure as a result of a goal based …