Engineering Commons^™

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 …

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, …

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 …

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 …