Electrical & Computer Engineering Doctoral Work

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Adaptive Beamforming for Antennas on General Wedge- and Cylindrical-Shaped Surfaces
(North Dakota State University, 2014) Irfanullah, Irfanullah
Adaptive beamforming antennas capable of accommodating the growing number of wireless subscribers throughout the world has become an essential part of modern wireless systems. In this work, the beamforming of a conformal antenna on a changing conformal surface is studied by relating the varying position of each antenna element in the array to the weighting coefficients (i.e, array weights) required to give a desired antenna beam formation. In particular, the beamforming of a 1 x 4 array on a changing wedge- and cylindrical-shaped surface is studied using the projection method on a wavefront of a transmitted wave in a particular direction. To validate the theory, a 1 x 4 prototype antenna with individual voltage-controlled phase shifters and attenuators is used to implement the computed weights of each individual antenna element for measurements in an anechoic chamber. Overall agreement between theory, simulations and measurements is shown throughout the work. Furthermore, the effects of mutual coupling and changing conformal surfaces on the behavior of the beamforming pattern and array weights is investigated and summarized.
Analyses, Mitigation and Applications of Secure Hash Algorithms
(North Dakota State University, 2020) Al-Odat, Zeyad Abdel-Hameed
Cryptographic hash functions are one of the widely used cryptographic primitives with a purpose to ensure the integrity of the system or data. Hash functions are also utilized in conjunction with digital signatures to provide authentication and non-repudiation services. Secure Hash Algorithms are developed over time by the National Institute of Standards and Technology (NIST) for security, optimal performance, and robustness. The most known hash standards are SHA-1, SHA-2, and SHA-3. The secure hash algorithms are considered weak if security requirements have been broken. The main security attacks that threaten the secure hash standards are collision and length extension attacks. The collision attack works by finding two different messages that lead to the same hash. The length extension attack extends the message payload to produce an eligible hash digest. Both attacks already broke some hash standards that follow the Merkle-Damgrard construction. This dissertation proposes methodologies to improve and strengthen weak hash standards against collision and length extension attacks. We propose collision-detection approaches that help to detect the collision attack before it takes place. Besides, a proper replacement, which is supported by a proper construction, is proposed. The collision detection methodology helps to protect weak primitives from any possible collision attack using two approaches. The first approach employs a near-collision detection mechanism that was proposed by Marc Stevens. The second approach is our proposal. Moreover, this dissertation proposes a model that protects the secure hash functions from collision and length extension attacks. The model employs the sponge structure to construct a hash function. The resulting function is strong against collision and length extension attacks. Furthermore, to keep the general structure of the Merkle-Damgrard functions, we propose a model that replaces the SHA-1 and SHA-2 hash standards using the Merkle-Damgrard construction. This model employs the compression function of the SHA-1, the function manipulators of the SHA-2, and the $10*1$ padding method. In the case of big data over the cloud, this dissertation presents several schemes to ensure data security and authenticity. The schemes include secure storage, anonymous privacy-preserving, and auditing of the big data over the cloud.
Analysis and Characterization of Cloud Based Data Center Architectures for Performance, Robustness, Energy Efficiency, and Thermal Uniformity
(North Dakota State University, 2014) Bilal, Kashif
Cloud computing is anticipated to revolutionize the Information and Communication Technology (ICT) sector and has been a mainstream of research over the last decade. Today, the contemporary society relies more than ever on the Internet and cloud computing. However, the advent and enormous adoption of cloud computing paradigm in various domains of human life also brings numerous challenges to cloud providers and research community. Data Centers (DCs) constitute the structural and operational foundations of cloud computing platforms. The legacy DC architectures are inadequate to accommodate the enormous adoption and increasing resource demands of cloud computing. The scalability, high cross-section bandwidth, Quality of Service (QoS) guarantees, privacy, and Service Level Agreement (SLA) assurance are some of the major challenges faced by today’s cloud DC architectures. Similarly, reliability and robustness are among the mandatory features of cloud paradigm to handle the workload perturbations, hardware failures, and intentional attacks. The concerns about the environmental impacts, energy demands, and electricity costs of cloud DCs are intensifying. Energy efficiency is one of mandatory features of today’s DCs. Considering the paramount importance of characterization and performance analysis of the cloud based DCs, we analyze the robustness and performance of the state-of-the-art DC architectures and highlight the advantages and drawbacks of such DC architecture. Moreover, we highlight the potentials and techniques that can be used to achieve energy efficiency and propose an energy efficient DC scheduling strategy based on a real DC workload analysis. Thermal uniformity within the DC also brings energy savings. Therefore, we propose thermal-aware scheduling policies to deliver the thermal uniformity within the DC to ensure the hardware reliability, elimination of hot spots, and reduction in power consumed by cooling infrastructure. One of the salient contributions of our work is to deliver the handy and adaptable experimentation tools and simulators for the research community. We develop two discrete event simulators for the DC research community: (a) for the detailed DC network analysis under various configurations, network loads, and traffic patterns, and (b) a cloud scheduler to analyze and compare various scheduling strategies and their thermal impact.
Analysis of Secrecy in Multi-User Wireless Network
(North Dakota State University, 2018) Ghosh, Anirban
We consider an Ergodic Fading Broadcast Channel with one Legitimate receiver and one Eavesdropper (BCoLoE) having arbitrary fading statistics, where the instantaneous Channel State Information (CSI) are known only at the receivers (CSIR). The secrecy capacity of this channel is characterized within 11 bits irrespective of fading statistics and Signal-to-Noise Ratios (SNRs). This is achieved by deriving a new upper bound to the secrecy capacity of the channel and two new lower bounds. The upper bound is derived by approximating Complementary Cumulative Distribution Functions (CCDFs) of the two links by corresponding staircase functions. The smaller lower bound, although looser, has a form which can be analytically compared with the upper bound and facilitates the approximate secrecy capacity characterization. It is proved that, the so called Binary Expansion Signaling with Reverse Stripping (BES-RS) scheme can achieve a secrecy rate larger than both these lower bounds with the help of numerical computation for several BCoLoEs with practical fading statistics. We further characterize the secrecy capacity of a class of 2-user binary fading interference channel (BFIC) and 2-user layered fading interference channel (LFIC), under the same assumptions as for the wiretap channel. The secrecy capacity region for a very weak BFIC turns out to be quadrangular while for LFIC it is polygonal. We explicitly characterize the corner points in both the cases. The converse in either case is proved by dividing the set of upper bounds into two carefully chosen regions depending on the values of ω - the weighting factor of the weighted sum bounds. In case of LFIC each of the regions are also shown to be piece-wise linear. The achievability on the other hand is proved by using capacity optimal code for a layered erasure wiretap channel at both the transmitters and treating interference as erasure while decoding the signals at the receivers. In addition, the achievability of the layered case also involves proper assignment of the layers to the two transmitters based on some constraints. We also prove the secrecy capacity of strong BFIC and LFIC as zero.
Bit Optimized Reconfigurable Network (BORN): A New Pathway Towards Implementing a Fully Integrated Band-Switchable CMOS Power Amplifier
(North Dakota State University, 2020) Hamidi Perchehkolaei, Seyyed Babak
The ultimate goal of the modern wireless communication industry is the full integration of digital, analog, and radio frequency (RF) functions. The most successful solution for such demands has been complementary metal oxide semiconductor (CMOS) technology, thanks to its cost-effective material and great versatility. Power amplifier (PA), the biggest bottleneck to integrate in a single-chip transceiver in wireless communications, significantly influences overall system performance. Recent advanced wireless communication systems demand a power amplifier that can simultaneously support different communication standards. A fully integrated single-chip tunable CMOS power amplifier is the best solution in terms of the cost and level of integration with other functional blocks of an RF transceiver. This work, for the first time, proposes a fully integrated band-switchable RF power amplifier by using a novel approach towards switching the matching networks. In this approach, which is called Bit Optimized Reconfigurable Network (BORN), two matching networks which can be controlled by digital bits will provide three operating frequency bands for the power amplifier. In order to implementing the proposed BORN PA, a robust high-power RF switch is presented by using resistive body floating technique and 6-terminal triple-well NMOS. The proposed BORN PA delivers measured saturated output power (Psat) of 21.25/22.25/ 23.0dBm at 960MHz/1317MHz/1750MHz, respectively. Moreover, the proposed BORN PA provides respective 3-dB bandwidth of 400MHz/425MHz/550MHz, output 1-dB compression point (P1dB) of 19.5dBm/20.0dBm/21.0dBm, and power-added efficiency (PAE) of 9/11/13% at three targeted frequency bands, respectively. The promising results show that the proposed BORN PA can be a practical solution for RF multiband applications in terms of the cost and level of integration with other functional blocks of an RF transceiver.
Carbon Microfiber Material for Electromagnetic (Shielding) Applications
(North Dakota State University, 2015) Rafiq, Muhammad Nadeem
Electromagnetic shielding is becoming more and more important with the abundance of wireless devices. Therefore a need has arisen for more versatile, flexible and low-cost solutions for shielding. For these requirements, carbon microfiber material has been proposed for electromagnetic shielding applications. For this purpose its shielding effectiveness has been measured and modeled in a simulation environment. A parametric simulation was conducted for the material property ’conductivity’ and the results were compared to measured ones. These simulation results were also verified by the analytical solution for the shielding effectiveness and the agreement between the simulated values and analytical results demonstrated that the carbon microfiber material, though having less conductivity than the traditional metallic shields is a good candidate for electromagnetic shielding applications. Carbon microfiber not only provides comparable shielding effectiveness to a metallic shield but it can be advantageous because of its light weight, corrosion resistance and flexibility. Also, its porous nature can help with cooling of enclosed electronic circuits.
Cardiac Output Improvement in Mechanical Circulatory Support Devices
(North Dakota State University, 2017) Qureshi, Muhammad Bilal
Mechanical circulatory support devices (MCSDs) have gained widespread clinical acceptance as an effective heart failure (HF) therapy. The concept of harnessing the kinetic energy (KE) available in the forward aortic flow (AOF) is proposed as a novel control strategy to further increase the cardiac output (CO) provided by MCSDs. A complete mathematical development of the proposed theory and its application to an example MCSDs (two-segment extra-aortic cuff) are presented. To achieve improved device performance and physiologic benefit, the example MCSD timing is regulated to maximize the forward AOF KE and minimize retrograde flow. The proof-of-concept was tested to provide support with and without KE control in a computational HF model over a wide range of HF test conditions. The simulation predicted increased stroke volume (SV) by 20% (9 mL), CO by 23% (0.50 L/min), left ventricle ejection fraction (LVEF) by 23%, and diastolic coronary artery flow (CAF) by 55% (3 mL) in severe HF at a heart rate (HR) of 60 beats per minute (BPM) during counterpulsation (CP) support with KE control. This research also explains how selection of inflation and deflation timing points for extra-aortic two-segmented cuff counterpulsation device (CPD) can affect the hemodynamic of the cardiovascular system (CVS). A comprehensive analysis of compliance profile timings generated through exhaustive search technique and the one selected through steepest descent method is carried out to predict and compare the difference in SV via computer simulation models. The influence of control modes (timing and duration) of deflation and inflation for extra-aortic two-segmented CPD on hemodynamic factors compared to no-assist HF were investigated. Simulation results (P < 0.05) predicted that the two-segmented CPD with late deflation and early inflation mode would be a suitable mode with 80% augmentation in peak diastolic aortic pressure (AOP), reduction in peak systolic pressure up to 15%, increases in CO by 60% and mean CAF by 80%. The proposed KE control concept may improve performance of other MCSDs to further enhance their potential clinical benefits, which warrants further investigation. The next step is to investigate various assist technologies and determine where this concept is best applied.
Characterization of a Structure Consisting of Magnetostatic Responsive Microscopic Particles and Its Applications In Antennas
(North Dakota State University, 2015) Iftikhar, Adnan
Wireless communication systems often require that a single antenna work at different frequencies. Thus the recon gurable antennas are useful in frequency agile environments to receive a signal over multiple bands. Research on antenna recon gurability using mechanical systems and radio frequency (RF) switches have been implemented in the past years. One problem for these voltage- controlled switches is that they require direct current (DC) bias control lines for operation. The incorporation of DC biasing circuitry also limits designers to explore the recon gurable capacity of many antennas. The DC bias control lines can possibly degrade the antenna performance. Moreover, because of the additional control signals, many existing multiband systems cannot use recon gurable antennas. In this research, magnetostatic responsive particles are used in micro-sized cavities to manufacture novel magnetic switches that are activated in a magnetic eld. Furthermore, the characterization, modeling in simulation software, and lumped element model extraction of these micro electromechanical systems (MEMS) based on magnetic switches is presented. A re ned method of quantifying the micro sized magnetic particles in a cavity and the response of the proposed micro level magnetic switches in the RF eld is also explained in detail. Then, a microstrip patch antenna loaded with Electromagnetic Band Gaps (EBGs) that cannot be recon gured using existing RF switching devices was recon gured using the proposed magnetic switches and is presented in this research for the rst time. A comparison between PIN diodes and the proposed magnetic switches on a microstrip patch is also included in this research to show the efficiency of the proposed structure. Overall, the proposed magnetic switches showed good results when used in antenna systems to achieve recon gurability and do not effect the radiation characteristics of the recon gured antenna.
Characterization of Inflationary and Deflationary Auscultatory Blood Pressure Measurements
(North Dakota State University, 2022) Alvarez, Enrique
This document is a paper-based dissertation. The dissertation is a collection of articles written by the author in the pursuit to develop a novel method to measure blood pressure (BP). The introduction chapter describes how the documents are interrelated. This work starts with the description of the development and design of a non-invasive medical device capable of measuring arterial BP with a combination of inflationary and deflationary procedures. In addition to the device, we conducted a human-based study to characterize the properties of the BP signal in the inflationary and deflationary curves. With the signals acquired, we focused on the uncertainty occurring when taking two consecutive BP measurements. The prototype was composed of 1) a modified off-the-shelf oscillometric BP system, 2) a contact microphone with an amplifier, and 3) a high-sensitivity pulse oximeter, and its control electronics. The device captured the cuff pressure signal, arterial skin-surface acoustics, and photoplethysmography (PPG). The captured signals were processed and analyzed. We focused our analysis on the characterization of the uncertainty of two consecutive BP measurements by studying the biosignals captured with the custom-made apparatus. Accurate non-invasive BP measurements are vital in preventing and treating many cardiovascular diseases. The “gold standard” for non-invasive procedures is the auscultatory method, which is based on detecting Korotkoff sounds while deflating an arm cuff. Using this method as a “gold standard” requires highly-trained technicians and has an intrinsic uncertainty in its BP predictions. In this document, we analyze and characterize the origins of BP uncertainty. By analyzing the captured bio signals we postulate an uncertainty model for two consecutive BP measurements. Our research group developed a computer-based simulation of auscultatory BP measurement uncertainty, and these modeled results were compared to a humansubject experiment with a group of 20 diverse-conditioned individuals. Uncertainties were categorized and quantified. The total computer-simulated uncertainty ranged between -8.4 mmHg to 8.4 mmHg in systolic BP and -8.4 mmHg to 8.3 mmHg in diastolic BP at a 95% confidence interval. The limits in the human-based study ranged from -8.3 mmHg to 8.3 mmHg in systolic BP and -16.7 mmHg to 4.2 mmHg in diastolic BP.
Cloud Based Recommendation Services for Healthcare
(North Dakota State University, 2016) Abbas, Assad
With the inception of portable computing devices, enormous growth in the healthcare data over the Internet has been observed. Consequently, the Web based systems come across several challenges, such as storage, availability, reliability, and scalability. By employing the cloud computing to offer healthcare services helps in overcoming the aforementioned challenges. Besides the healthcare organizations, cloud computing services are also equally beneficial for general public in devising patient-centric or user-centric methodologies that involve users in managing health related activities. This dissertation proposes methodologies to: (a) make risk assessment about diseases and to identify health experts through social media using cloud based services, (b) recommend personalized health insurance plans, and (c) secure the personal health data in the cloud. The proposed disease risk assessment approach compares the profiles of enquiring users with the existing disease specific patient profiles and calculates the risk assessment score for that disease. The health expert consultation service permits users to consult with the health specialists that use Twitter by analyzing the tweets. The methodology employs Hyperlink-Induced Topic Search (HITS) based approach to distinguish between the doctors and non-doctors on the basis of tweets. For personalized health insurance plans identification, a recommendation framework to evaluate different health insurance plans from the cost and coverage perspectives is proposed. Multi-attribute Utility Theory (MAUT) is used to permit users evaluate health insurance plans using several criteria, for example premium, copay, deductibles, maximum out-of-pocket limit, and various other attributes. Moreover, a standardized representation of health insurance plans to overcome the heterogeneity issues is also presented. Furthermore, the dissertation presents a methodology to implement patient-centric access control over the patients’ health information shared in the cloud environment. This methodology ensures data confidentiality through the El-Gamal encryption and proxy re-encryption approaches. Moreover, the scheme permits the owners of health data to selectively grant access to users over the portions of health records based on the access level specified in the Access Control List (ACL) for different groups of users. Experimental results demonstrate the efficacy of the methodologies presented in the dissertation to offer patient/user-centric services and to overcome the scalability issues.
A Compact Cylindrical-Shape Microstrip Structure with Cloaking Properties for Mutual Coupling Reduction in Array Antennas
(North Dakota State University, 2014) Naqvi, Syed Aftab
A cylindrical-shaped microstrip structure with cloaking properties is presented as a shielding device to reduce the mutual coupling between two patch antennas. The surface comprises of a number of 2-port microstrip (2-PM) elements printed on individual substrates and, to enclose a particular region, several 2-PM elements are interconnected into a cylindrical shape. Each 2-PM element has the capability of coupling an incident EM field on the surface to the adjacent interconnected elements. Then, because the 2-PM elements are connected into a cylindrical shape, the incident EM field is re-radiated from the other interconnected 2-PM elements in a direction away from the transmitter; achieving a behavior similar to a cloak. The prototypes in this dissertation illustrates that this surface has the additional benefit of overcoming many of the manufacturing difficulties of traditional cloaks because microstrip structures are used. To demonstrate this concept, a cylindrical surface operating at 3.89 GHz and a frequency reconfigurable surface (consisting of 2-port frequency reconfigurable microstrip elements (2-PFRM)) operating at 3.68 GHz and 3.89 GHz is simulated in HFSS, manufactured and measured in a full anechoic chamber. Moreover, as an application, the cylindrical surface operating at 3.89 GHz is used to reduce the mutual coupling between two patch antennas operating simultaneously at 3.89 GHz. The radiation pattern and the gain of a 2-element array is measured to demonstrate the negligible effects of a cylindrical surface on the far field antenna array parameters. Simulation and measurement results are in good agreement and validate the proposed EM cloak-based surface for applications such as antenna array shielding, radar cross section and communications in complex EM environments.
Conformal Antennas and Arrays with Layers Consisting of Copper and Graphene-based Conductors for Redundancy Properties
(North Dakota State University, 2017) Sajal, Sayeed Zebaul Haque
Graphene is a new promising material with unique electrical, mechanical, optical and thermal characteristics. The use of graphene in the design of an antenna and other electromagnetic passive devices would be beneficial for miniaturization, efficient dynamic tuning, monolithic integration with graphene RF nano-electronics, and even transparency, mechanical flexibility, andreliability. However, there are some challenges to fabricate and design an antenna with pure graphene embedded in the layout. Here, an advanced study on the electrical and mechanical properties of the graphene-based conductive material (not pure graphene), and how this material can be utilized in developing a first-ever graphene-based conformal antenna array for wireless communication systems has been done. More specifically, the important factors for antenna design, such as electrical and mechanical properties, will be studied here to ensure an effective and efficient design. Next, a graphene-based antenna array on a planar surface will be designed to validate the electrical and mechanical properties, and finally, the trade-off of the graphene-based antenna array on a conformal surface is investigated. To mitigate the challenges of designing a graphene-based conformal antenna array, proper care is needed to achieve the optimal performance of the antenna array system. These new mechanisms of the graphene-based conformal antenna arrays will bring new possibilities in conformal antenna usage and wearable antenna applications for the first time.
Contextualization in Large-Scale Social Networks
(North Dakota State University, 2014) Irfan, Rizwana S.
Social computing-based applications provide a coherent medium through which people can be interactive and socialize by developing a Web-based communication channel that integrates different Social Networking Services (SNSs) in the Social Networking Platforms (SNPs). Different SNSs, such as photo, audio, and video sharing, have emerged as an essential resources for the dissemination of information about the human interaction patterns. Most of the SNSs are integrated into a comprehensive and coherent paradigm called the Social Networking Platform (SNP). Most of the existing SNSs focused on content-based, media-based, and geo-location-based approach. The content-based SNSs allow the text-based interactions among individuals, such as communities, blogs, and social news. The media-based SNSs provide the social interaction through various multimedia formats, such as video and audio. Geo-location-based SNSs provide location-based social communication. However, all of the aforementioned techniques lack the semantic analysis which is the most integral and crucial part of the true understanding. The goal of this dissertation is to incorporate the existing SNSs into the context-enriched information that provide the services customization based on the individual human characteristics, such as human preferences, and emotions. The computer interactive infrastructure can be enriched by leveraging information about the users’ personal context (profile, preferences, attitude, and habits) that provides sophisticated context-aware services, such as semantic-based search and context-aware recommendations. The dissertation proposes MobiContext, a cloud-based Bi-Objective Recommendation Framework (BORF) for mobile social networks that generates real-time recommendation of venues for a group of mobile users. The MobiContext utilizes multi-objective optimization techniques to generate personalized recommendations. To address the issues pertaining to cold start and data sparseness, the BORF performs data preprocessing by using the Hub-Average (HA) inference model. Moreover, the Weighted Sum Approach (WSA) is implemented for scalar optimization and an evolutionary algorithm (NSGA-II) is applied for vector optimization to provide optimal suggestions to the users about a venue. The dissertation also proposes a SocialRec, a context-aware recommendation framework that utilizes a rating sentiment inference approach to incorporate textual users’ review into traditional collaborative filtering methods for personalized recommendations. The proposed framework utilizes semantic analysis scores on the users’ contextual information to produce optimal recommendations.
Creation and Implementation of the Innovation-Based Learning Framework: A Learning Analytics Approach
(North Dakota State University, 2022) Singelmann, Lauren
To meet the national and international call for creative and innovative engineers, many engineering departments and classrooms are striving to create more authentic learning spaces where students are actively engaging with design and innovation activities. For example, one model for teaching innovation is Innovation-Based Learning (IBL) where students learn fundamental engineering concepts and apply them to an innovation project with the goal of producing value outsidethe classroom. The model has been fairly successful, but questions still remain about how to best support students and instructors in open-ended innovation spaces. To answer these questions, learning analytics and educational data mining (LA/EDM) techniques were used to better understand student innovation in IBL settings. LA/EDM is a growing field with the goal of collecting and interpreting large amounts of educational data to support student learning. In this work, five LA/EDM algorithms and tools were developed: 1) the IBL framework which groups student actions into illustrative categories specific to innovation environments, 2) a classifier model that automatically groups student text into the categories of the framework, 3) classifier models that leverage the IBL framework to predict student success, 4) clustering models that group students with similar behavior, and 5) epistemic network analysis models that summarize temporal student behavior. For each of the five algorithms/tools, the design, development, assessment, and resulting implications are presented. Together, the results paint a picture of the affordances and challenges of teaching and learning innovation. The main insights gained are how language and temporal behavior provide meaningful information about students’ learning and innovation processes, the unique challenges that result from incorporating open-ended innovation into the classroom, and the impact of using LA/EDM tools to overcome these challenges.
Design and Analysis of New Printed Wideband Antennas for Wireless Applications
(North Dakota State University, 2014) Asirvatham, Koby
In this study a simple method to develop a wideband antenna is proposed. With this new technique a dipole antenna with a 48% frequency bandwidth is transformed to achieve a 120% frequency bandwidth for a voltage standing-wave ratio ≤ 2. Two different designs are tested and their performance is compared: the segmented-ring antenna and the split-ring antenna. Both antennas achieved a stable radiation pattern and a moderate gain. Nearly omnidirectional radiation patterns have been observed in both the XZ and YZ-planes. Finally, simple passive arrays are presented, demonstrating the usefulness of the split-ring antenna as an array element. Beam steering is demonstrated with a four element passive array using horizontal meandering lines. This novel antenna has wide applications in high-capacity wireless communication system.
Detection and Quantification of Rare Analytes in Biological Samples using Dielectrophoretic Spectroscopy
(North Dakota State University, 2017) Kirmani, Syed Abdul Mannan
Novel techniques for Dielectrophoresis (DEP) crossover frequency calculation, positive dielectrophoretic spectroscopy and negative dielectrophoretic spectroscopy are proposed in this dissertation. A novel automated immunoassay based on negative dielectrophoretic spectroscopy for the detection and quantification of rare-analytes in a biological sample is also presented. All of these techniques are based on a custom made automated software “DEP spectroscopy application” for Microsoft Windows that was designed and developed for this research project. The techniques for DEP crossover frequency calculation and dielectrophoretic spectroscopy were validated through experiments with blue colored polystyrene beads with 1000 nm diameter. The techniques for positive dielectrophoretic spectroscopy and negative dielectrophoretic spectroscopy were validated through experiments with fluorescent polystyrene beads with 500 nm diameter. An increase in negative DEP force was observed in response to the increase in the frequency of the applied electric field. This increased DEP force resulted in higher speed of repulsion of functionalized polystyrene beads from the edge of the electrode. The speed of repulsion was measured for 0%, 0.8%, 50% and 100% conjugation of avidin with biotin functionalized polystyrene beads with the automated software through real-time image processing. A significant difference in the velocity of the beads was observed among different avidin-biotin conjugation concentrations that can be used to quantify rare analytes in a biological sample. Using this technique, as little as 80 molecules of avidin per biotin functionalized bead can be detected in a sample. This technology can be applied to the detection and quantification of rare analytes that can be useful in the diagnosis and treatment of diseases like cancer and myocardial infarction with the use of polystyrene beads functionalized with antibodies for the target biomarkers.
Development of Performance Optimized Rotation Tolerant Viola-Jones Based Blackbird Detection, a Throughput Optimized Asynchronous Mac Implementation, and Automated Wheat Lodging Estimation
(North Dakota State University, 2020) Jalil, Nauman
The research described in this doctoral dissertation focuses on three main topics:1) performance optimization of the Viola-Jones Algorithm (VJA) for red-winged blackbird (Agelaius phoeniceus) detection, 2) further increasing performance of an already optimized asynchronous Multiply and Accumulate (MAC) unit, and 3) development of a framework to differentiate between lodging and non-lodging areas of a field from visible and multispectral aerial drone images. The first topic explores VJA rotational robustness, since VJA object detection is inherently not invariant to in-plane object rotation. An efficient method to detect rotated blackbirds is developed, which provides a balance between detection accuracy and computational cost. The second topic further optimizes a previously developed high-speed asynchronous 72+32×32 MAC, which was the fastest in the literature, resulting in a speedup of 1.36 while also decreasing area by 8%. The third topic develops a model to distinguish lodging from non-lodging plots, using a Support Vector Machine model trained with color, texture, Normalized Difference Vegetation Index (NDVI), and height features. The model prediction accuracy is around 90%, indicating good performance in distinguishing lodging from non-lodging plots.
Dynamic State Estimation Assisted Power System Monitoring and Protection
(North Dakota State University, 2016) Cui, Yinan
The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of “Dynamic State Estimation” (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the energy function for the system. This establishes a direct correspondence (or mapping) between an event and certain component(s) of the energy function. The last paper considers the dynamic latency effect when the measurements and estimated dynamics are transmitted from remote ends to a centralized location through the networks.
Efficient Message Dissemination Framework for Diverse Wireless Networks
(North Dakota State University, 2014) Khalid, Osman
Wireless networks exhibit diversity, ranging from mostly disconnected delay tolerant networks and partially connected mobile ad hoc networks, to mostly connected cellular networks. Besides having useful applications, including, vehicular communications, emergency response networks, battlefield networks, and wildlife monitoring, wireless networks face numerous challenges, such as unreliable connectivity, bandwidth restrictions, interference, frequent disruptions and delays, power outages, message loss, and malicious attacks. Moreover, when nodes are mobile, communication may be disrupted frequently for longer time periods. Designing protocols to tolerate such disruptions is challenging because of the extreme uncertainty in mobile wireless environments. Most of the existing approaches either require exact knowledge about future connectivity schedules, or perform message flooding in an attempt to improve message delivery rate. However, message flooding results in an increased overhead and loss of messages in resource constrained environments. Moreover, it is almost impossible to acquire precise future contact schedules in real-life scenarios. The goal of this dissertation is to architect robust protocols that overcome disruptions and enable applications in diverse wireless networks. We propose a suite of protocols for wireless environments where nodes transfer messages during opportunistic contacts. To conserve resources, the protocols control flooding by autonomously adapting to the changing network conditions, to find optimal temporal routes between source and destination nodes. Moreover, the dissertation presents novel approaches that utilize time-series forecasting on nodes’ contact patterns. Such routing schemes learn from nodes’ temporal contacts and mobility patterns, and forecasts the future contact opportunities among the nodes. By making precise predictions about future contacts, messages are forwarded to only those nodes that increase the message delivery likelihood. Simulation results proved that the proposed routing framework can be efficiently utilized in many real-life applications to disseminate delay tolerant data, such as electronic newspapers, weather forecasts, movie trailers, emergency information, and travel routes information in various parts of a city. The dissertation also proposes a novel application for mobile social networks that generates real-time recommendation of venues for a group of mobile users. The proposed framework utilizes Ant colony algorithm, social filtering, and hub and authority scores on the users’ contextual information to produce optimal recommendations.
Embracing Visual Experience and Data Knowledge: Efficient Embedded Memory Design for Big Videos and Deep Learning
(North Dakota State University, 2019) Edstrom, Jonathon
Energy efficient memory designs are becoming increasingly important, especially for applications related to mobile video technology and machine learning. The growing popularity of smart phones, tablets and other mobile devices has created an exponential demand for video applications in today’s society. When mobile devices display video, the embedded video memory within the device consumes a large amount of the total system power. This issue has created the need to introduce power-quality tradeoff techniques for enabling good quality video output, while simultaneously enabling power consumption reduction. Similarly, power efficiency issues have arisen within the area of machine learning, especially with applications requiring large and fast computation, such as neural networks. Using the accumulated data knowledge from various machine learning applications, there is now the potential to create more intelligent memory with the capability for optimized trade-off between energy efficiency, area overhead, and classification accuracy on the learning systems. In this dissertation, a review of recently completed works involving video and machine learning memories will be covered. Based on the collected results from a variety of different methods, including: subjective trials, discovered data-mining patterns, software simulations, and hardware power and performance tests, the presented memories provide novel ways to significantly enhance power efficiency for future memory devices. An overview of related works, especially the relevant state-of-the-art research, will be referenced for comparison in order to produce memory design methodologies that exhibit optimal quality, low implementation overhead, and maximum power efficiency.

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