Digital Commons Network^™

Surface Enhanced Raman Scattering (Sers) Substrates And Probes, Srismrita Basu

LSU Doctoral Dissertations

Raman spectroscopy is a well-known technique for complex molecular detection. In Raman spectrometry, laser beam is focused on a sample to generate a unique "fingerprint" of the molecule. The Raman signal is very weak. To overcome this problem nano rough metallic substrates are fabricated to enhance the signal strength. In clinical applications, remote contact and minimally invasive probes inside the specimen are needed.

This research work is divided in: (1) development of Surface Enhanced Raman Scattering (SERS) substrate using gold coated etched aluminum foil, (2) development of the SERS probe using the aluminum based substrate with a single optical fiber …

Microgrid Energy Management With Flexibility Constraints: A Data-Driven Solution Method, Okan Ciftci

LSU Master's Theses

Microgrid energy management is a challenging and important problem in modern power systems. Several deterministic and stochastic models have been proposed in the literature for the microgrid energy management problem. However, more accurate models are required to enhance flexibility of the microgrids when accounting for renewable energy and load uncertainties. This thesis proposes key contributions to solve the energy management problem for smart building (or small-scale microgrid). In Chapter 3, a deterministic energy management model is presented taking into account system flexibility requirements. Energy storage systems are deployed to enhance the grid flexibility and ramping capability. The objective function of …

A Study Of Very Short Intermittent Ddos Attacks On The Performance Of Web Services In Clouds, Huasong Shan

LSU Doctoral Dissertations

Distributed Denial-of-Service (DDoS) attacks for web applications such as e-commerce are increasing in size, scale, and frequency. The emerging elastic cloud computing cannot defend against ever-evolving new types of DDoS attacks, since they exploit various newly discovered network or system vulnerabilities even in the cloud platform, bypassing not only the state-of-the-art defense mechanisms but also the elasticity mechanisms of cloud computing.

In this dissertation, we focus on a new type of low-volume DDoS attack, Very Short Intermittent DDoS Attacks, which can hurt the performance of web applications deployed in the cloud via transiently saturating the critical bottleneck resource of the …

Modeling Of Thermally Aware Carbon Nanotube And Graphene Based Post Cmos Vlsi Interconnect, K M Mohsin

LSU Doctoral Dissertations

This work studies various emerging reduced dimensional materials for very large-scale integration (VLSI) interconnects. The prime motivation of this work is to find an alternative to the existing Cu-based interconnect for post-CMOS technology nodes with an emphasis on thermal stability. Starting from the material modeling, this work includes material characterization, exploration of electronic properties, vibrational properties and to analyze performance as a VLSI interconnect. Using state of the art density functional theories (DFT) one-dimensional and two-dimensional materials were designed for exploring their electronic structures, transport properties and their circuit behaviors. Primarily carbon nanotube (CNT), graphene and graphene/copper based interconnects were …

Hierarchical Fusion Based Deep Learning Framework For Lung Nodule Classification, Kazim Sekeroglu

LSU Doctoral Dissertations

Lung cancer is the leading cancer type that causes the mortality in both men and women. Computer aided detection (CAD) and diagnosis systems can play a very important role for helping the physicians in cancer treatments. This dissertation proposes a CAD framework that utilizes a hierarchical fusion based deep learning model for detection of nodules from the stacks of 2D images. In the proposed hierarchical approach, a decision is made at each level individually employing the decisions from the previous level. Further, individual decisions are computed for several perspectives of a volume of interest (VOI). This study explores three different …

Information Theoretic Study Of Gaussian Graphical Models And Their Applications, Ali Moharrer

LSU Doctoral Dissertations

In many problems we are dealing with characterizing a behavior of a complex stochastic system or its response to a set of particular inputs. Such problems span over several topics such as machine learning, complex networks, e.g., social or communication networks; biology, etc. Probabilistic graphical models (PGMs) are powerful tools that offer a compact modeling of complex systems. They are designed to capture the random behavior, i.e., the joint distribution of the system to the best possible accuracy. Our goal is to study certain algebraic and topological properties of a special class of graphical models, known as Gaussian graphs. First, …

Implementing Spatial Symmetry In The Tensor Contraction Engine, Kevin Hartline

Honors Theses

No abstract provided.

Channel Estimation And Symbol Detection In Massive Mimo Systems Using Expectation Propagation, Kamran Ghavami

LSU Doctoral Dissertations

The advantages envisioned from using large antenna arrays have made massive multiple- input multiple-output systems (also known as massive MIMO) a promising technology for future wireless standards. Despite the advantages that massive MIMO systems provide, increasing the number of antennas introduces new technical challenges that need to be resolved. In particular, symbol detection is one of the key challenges in massive MIMO. Obtaining accurate channel state information (CSI) for the extremely large number of chan- nels involved is a difficult task and consumes significant resources. Therefore for Massive MIMO systems coherent detectors must be able to cope with highly imperfect …

Distributed Kalman Filters Over Wireless Sensor Networks: Data Fusion, Consensus, And Time-Varying Topologies, Jianming Zhou

LSU Doctoral Dissertations

Kalman filtering is a widely used recursive algorithm for optimal state estimation of linear stochastic dynamic systems. The recent advances of wireless sensor networks (WSNs) provide the technology to monitor and control physical processes with a high degree of temporal and spatial granularity. Several important problems concerning Kalman filtering over WSNs are addressed in this dissertation. First we study data fusion Kalman filtering for discrete-time linear time-invariant (LTI) systems over WSNs, assuming the existence of a data fusion center that receives observations from distributed sensor nodes and estimates the state of the target system in the presence of data packet …

Protection Challenges Of Distributed Energy Resources Integration In Power Systems, Pooria Mohammadi

LSU Doctoral Dissertations

It is a century that electrical power system are the main source of energy for the societies and industries. Most parts of these infrastructures are built long time ago. There are plenty of high rating high voltage equipment which are designed and manufactured in mid-20th and are currently operating in United States’ power network. These assets are capable to do what they are doing now. However, the issue rises with the recent trend, i.e. DERs integration, causing fundamental changes in electrical power systems and violating traditional network design basis in various ways. Recently, there have been a steep rise in …

Modeling Of Two Dimensional Graphene And Non-Graphene Material Based Tunnel Field Effect Transistors For Integrated Circuit Design, Md Shamiul Fahad

LSU Doctoral Dissertations

The Moore’s law of scaling of metal oxide semiconductor field effect transistor (MOSFET) had been a driving force toward the unprecedented advancement in development of integrated circuit over the last five decades. As the technology scales down to 7 nm node and below following the Moore’s law, conventional MOSFETs are becoming more vulnerable to extremely high off-state leakage current exhibiting a tremendous amount of standby power dissipation. Moreover, the fundamental physical limit of MOSFET of 60 mV/decade subthreshold slope exacerbates the situation further requiring current transport mechanism other than drift and diffusion for the operation of transistors. One way to …

Network Performance Analysis Using Cisco Virl, Charitra Maharjan

LSU Master's Theses

This thesis provides a detailed analysis of the effects of TCP and UDP traffic over a LAN and WAN medium. In addition, it also analyses some real time applications like audio, video and web browsing that is affected by TCP traffic while sharing a bottleneck node and/or link resources. As network industry is growing continuously, the network administrator should be aware of TCP and UDP traffic that is traversing through their network. The analysis and monitoring of the traffic is crucial as it directly affects the performance of the network. Finding a cause for the poor performance of the network …

Quantitative Estimation Of Causality And Predictive Modeling For Precipitation Observation Sites And River Gage Sensors, Tri Vu Nguyen

LSU Master's Theses

This project seeks to investigate two questions: correlations from precipitation measurement sensors to river gage sensors, and predictive modeling of peak river gage heights during precipitation events. First, if correlations can be quantified, then a predictive model can be explored to predict peak water levels at river gage sensors, in response to precipitation inputs. Answering both research questions can provide early flood detection benefits and provide quantitative time assessments for flood risks. An extensive data-driven study was conducted across a geographical area of the U.S, spanning the time period 2008-2016 to identify river gage sensors that are closely correlated to …

Improved Subset Generation For The Mu-Decoder, Utsav Agarwal

LSU Master's Theses

The MU-Decoder is a hardware subset generator that finds use in partial reconfiguration of FPGAs and in numerous other applications. It is capable of generating a set S of subsets of a large set Z_n with n elements. If the subsets in S satisfy the “isomorphic totally- ordered property”, then the MU-Decoder works very efficiently to produce a set of u subsets in O(log n) time and Θ(n √u log n) gate cost. In contrast, a vain approach requires Θ(un) gate cost. We show that this low cost for the MU-Decoder can be achieved without the isomorphism constraint, thereby allowing …

Aperiodic Multilayer Graphene Based Tunable And Switchable Thermal Emitter At Mid-Infrared Frequencies, Safura Sharifi

LSU Master's Theses

Over the past few decades, there have been tremendous innovations in electronics and photonics. The development of these ultra-fast growing technologies mostly relies on fundamental understanding of novel materials with unique properties as well as new designs of device architectures with more diverse and better functionalities. In this regard, the promising approach for next-generation nanoscale electronics and photonics is to exploit the extraordinary characteristics of novel nanomaterials. There has been an explosion of interest in graphene for photonic applications as it provides a degree of freedom to manipulate electromagnetic waves. In this thesis, to tailor the broadband blackbody radiation, new …

Estimation Of Rfid Tag Population Size By Gaussian Estimator, Md Mahmudul Hasan

LSU Master's Theses

Radio Frequency IDenti cation (RFID) systems are prevalent in all sorts of daily life endeavors. In this thesis we propose a new method to estimate RFID tag population size. We have named our algorithm "Gaussian Estimation of RFID Tags,"namely, GERT. We present GERT under both {0,1} and {0,1,e} channel models, and in both cases the estimator we use is a well justi ed Gaussian random variable for large enough frame size based on Central Limit Theorem for triangular arrays. The most prominent feature of GERT is the quality with which it estimates a tag population size. We support all the …

Photo-Effects On Current Transport In Back-Gate Graphene Field-Effect Transistor, Xinlu Chen

LSU Master's Theses

Graphene, which has attracted wide attention because of its two-dimensional structure and high carrier mobility, is a promising candidate for potential application in optics and electronics. In this dissertation, the photonic effects on current transport in back-gate graphene field-effect transistor is investigated. Chemical vapor deposition (CVD) on metal provides a promising way for large area, controllability and high quality graphene film. The transfer and back-gate transistor fabrication processes are proposed in this dissertation. The theoretical analysis of photodetector based on back-gate graphene field-effect transistor has been done. It is shown that the photo-electronic current consists of current contributions from photovoltaic, …

Experimental Study Of Frequency Oscillations In Islanded Power System, Kevin Daniel Wellman

LSU Master's Theses

Since the introduction of power electronics to the grid, the power system has quickly changed. Fault detection and removal is performed more accurately and at quicker response time, and non-inertia driven loads have been added. This means stability must continue to be a main topic of concern to maintain a stable synchronized grid. In this thesis a lab was designed, constructed, and tested for the purpose of studying transient stability in power systems. Many different options were considered and researched, but the focus of this paper is to describe the options chosen. The lab must be safe to operate and …

Analysis And Optimization Of Scientific Applications Through Set And Relation Abstractions, M. Tohid (Rastegar Tohid, Mohammed)

LSU Doctoral Dissertations

Writing high performance code has steadily become more challenging since the design of computing systems has moved toward parallel processors in forms of multi and many-core architectures. This trend has resulted in exceedingly more heterogeneous architectures and programming models. Moreover, the prevalence of distributed systems, especially in fields relying on supercomputers, has caused the programming of such diverse environment more difficulties. To mitigate such challenges, an assortment of tools and programming models have been introduced in the past decade or so. Some efforts focused on the characteristics of the code, such as polyhedral compilers (e.g. Pluto, PPCG, etc.) while others …

Microcavity Enhanced Beaming And Magneto-Optical Switching Of Light, Ali Haddadpour

LSU Doctoral Dissertations

In this dissertation, we show numerically that a compact structure, consisting of multiple optical microcavities at both the entrance and exit sides of a subwavelength plasmonic slit, can lead to greatly enhanced directional transmission through the slit. The microcavities increase the resonant enhancement of the emission in the normal direction and/or the coupling between free space waves and the slit mode. An optimized structure with two microcavities on both the entrance and exit sides of the slit leads to ~ 16 times larger transmission cross section per unit angle in the normal direction compared to the optimized reference slit without …

A New Computational Framework For Efficient Parallelization And Optimization Of Large Scale Graph Matching, Sahar Marefat Navaz

LSU Doctoral Dissertations

There are so many applications in data fusion, comparison, and recognition that require a robust and efficient algorithm to match features of multiple images. To improve accuracy and get a more stable result is important to take into consideration both local appearance and the pairwise relationship of features. Graphs are a powerful and flexible data structure, allowing for the description of complex relationships between data elements, whose nodes correspond to salient features and edges correspond to relational aspects between features. Therefore, the problem of graph matching is to find a mapping between the two sets of nodes that preserves the …