Other Electrical and Computer Engineering Commons^™

Developing Workflows For Passive Acoustic Detection Of Bedload Transport, Quinn Morgan

Dissertations and Theses

Bedload transport is defined as the amount of sediment, including gravel and rocks, traveling down stream. Monitoring bedload transport is important for river safety, hydrological studies and conservation efforts. Existing methods of directly measuring bedload transport (or bedload flux) involve lowering a collection device into a river and measuring the sediment collected; which can be expensive and time consuming. Hydroacoustic sensors, such as hydrophones, have had success tracking bedload flux remotely. This works by measuring the relatively high frequency of sediment impacts to map onto total bedload transported. No perfected method for detection of sediment generated noise (SGN) currently exists. …

Price-Signal-Based Control Strategy For Heat Pump Water Heaters In Demand Response Applications, Othman A. Murad

Dissertations and Theses

This work presents a price-signal-based control strategy for residential Heat Pump Water Heaters (HPWHs) aimed at reducing electricity costs and shifting load away from high-price periods. By integrating the California Load Flexibility Research and Development Hub (CalFlexHub) prototype price signals, the Consumer Technology Association (CTA-2045-B) communication protocol, and the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) simulation framework, a rule-based controller was developed to align HPWH operation with dynamic electricity pricing while maintaining hot water availability.

The control strategy was evaluated through two case studies: one using a fixed water draw profile under varying levels of price signal foresight, and another …

Renewable Energy Integration In Nyc Subway: Solar Panels (Under Railroads And At The Subway's Edge) & Vertical Axis Wind Turbines (Vawts) Near Tracks, Pengdwinde Olivier Saba

Dissertations and Theses

As urban populations continue to expand, the demands on public transit systems in densely populated regions like New York City are escalating. Multiple cities face the dual challenge of increasing ridership and the imperative to minimize their environmental footprints.According to Law 97 in NYC, the goal is to reduce emissions by 40% and to reach net zero by 2050. An innovative solution will need to be integrated into the NYC environment, such as the subway system, where there are a potential unuse space, building rooftop, since we know that spaces in New York City are very critical, such as these …

Blockchain Based Framework For Secure And Decentralized Energy Trading - Transforming Local Energy Markets For Sustainable Communities, Saurabh Sachdeva

Dissertations and Theses

The emergence of prosumers provides an opportunity for the setup of a local energy market (LEM) where individual households with distributed energy resources (DERs) can produce, store, and trade energy. Peer-to-peer(P2P) and decentralized energy trading (ET) can be implemented between the participants within or across microgrids. Several solutions based on the existing technologies have been proposed worldwide for the integration of prosumers in the existing energy setup and to enable and support ET, but these solutions present the issues of centralization, data integrity, and confidentiality, user and anonymity, and transparency. The applications of blockchain technology have recently become fascinating for …

Lidar Remote Sensing Of Aerosol And Ozone Profiles And Application To Air Quality Studies In New York City Area, Dingdong Li

Dissertations and Theses

Ozone (O₃) and PM2.5 (Particulate Matter with a diameter less than 2.5 μm) are the main pollutants in New York City (NYC) due to high levels of anthropogenic emissions, complex urban meteorology, and regional transport. However, vertical distribution observations are still lacking. This thesis utilizes lidar remote sensing techniques to retrieve the vertical distribution of O₃ and aerosols and study air pollution episodes in the NYC metropolitan area.

The thesis includes three parts. The first part analyzes continuous ceilometer observations of aerosols and atmospheric mixed-layer height (ML). We investigate the vertical, diurnal, and seasonal characteristics of the …

Use Of Battery Systems For Var Support In Con Edison’S Distribution Network/Substation, Elihu Nyemah

Dissertations and Theses

Battery Energy Storage System (BESS) can facilitate the integration of Distributed Energy Resources (DER) and help create a more reliable grid by providing multiple services including reactive power (VAR) support. This research will investigate the use of smart inverters to provide VAR support, assess the impact it has on the lifetime of a BESS and determine how the adverse effects (if any) can be mitigated/eliminated. To achieved this, a 7.5MW/30MWh grid connected BESS located at Con Edison substations have been modeled in MATLAB/Simulink. Preliminary assessment of the system showed that DC current to/from the battery is oscillating (non-zero) during reactive …

Ai-Driven Automated Medical Imaging Analysis, Jingya Liu

Dissertations and Theses

Medical imaging has been applied widely in many clinical diagnoses to detect and differentiate abnormalities by revealing the internal structure of the human body at normal anatomical and physiological levels. Manual analyzing medical images demands attention and is time-consuming, requiring well-trained expertise. The speed, fatigue, and experience may limit the diagnostic performance, leading to delays and even false diagnoses that significantly impact patient treatment. Therefore, accurate systematic systems based on medical image analysis are crucial for timely clinical diagnosis.

This dissertation focuses on advancing automatic computer-aided diagnosis systems to detect cancer, assisting radiologists with early intervention to improve survival rates. …

Blockchain-Based Architecture For Secured Cyberattack Signatures And Features Distribution, Oluwaseyi J. Ajayi

Dissertations and Theses

One effective way of detecting malicious traffic in computer networks is intrusion detection systems (IDS). Despite the increased accuracy of IDSs, distributed or coordinated attacks can still go undetected because of the single vantage point of the IDSs. Due to this reason, there is a need for attack characteristics' exchange among different IDS nodes. Another reason for IDS coordination is that a zero-day attack (an attack without a known signature) experienced in organizations located in different regions is not the same. Collaborative efforts of the participating IDS nodes can stop more attack threats if IDS nodes exchange these attack characteristics …

Challenges To Adopting Hybrid Methodology: Addressing Organizational Culture And Change Control Problems In Enterprise It Infrastructure Projects, Harishankar Krishnakumar

Dissertations and Theses

IT infrastructure projects have long been an overlooked field superseded by the more popular software development silos and cross-functional project teams when it comes to enterprise Agile transformations. This paper presents a systematic literature review by leveraging a qualitative research methodology based on empirical evidence provided in contemporary scholarly research articles to explore how certain variables such as organizational culture- including team structure, leadership hierarchy, geolocation, etc. along with an organization’s change management processes affect the adoption of a Hybrid/Agile project management methodology, focusing on reported challenges and critical success factors that define such large-scale enterprise transformations. The salient features …

Unique Image Representation As A Tensor, Bharat Rosanlall

Dissertations and Theses

This thesis presents a two dimensional orthonormal transform that represents an image as coefficients in 4 independent channels. The salient feature of these coefficients is that they contain complete position spatial frequency information about the image, in a sense that the original image can be reconstructed from these coefficients with negligible error. These coefficients can be used in various machine learning, AI , and other tasks where data features are used. Popular convolutional layer used in various neural networks reduces information and can not reconstruct original image. In this thesis , we present several examples where these coefficients are used …

Ict-Enabled Control And Energy Management Of Community Microgrids For Resilient Smart Grid Operation, Mahmoud Saleh

Dissertations and Theses

Our research has focused on developing novel controllers and algorithms to enhance the resilience of the power grid and increase its readiness level against major disturbances.

The U.S. power grid currently encounters two main challenges: (1) the massive and extended blackouts caused by natural disasters, such as hurricane Sandy. These blackouts have raised a national call to explore innovative approaches for enhanced grid resiliency. Scrutinizing how previous blackouts initiated and propagated throughout the power grid, the major reasons are lack of situational awareness, lack of real-time monitoring and control, underdeveloped controllers at both the transmission and distribution levels, and lack …

Sniffing, Decoding And Decryption Of Gsm Signals Using Low Cost Hardware And Open-Source Software, Muhammad Talha Choudhry

Dissertations and Theses

We have participated in the creation of almost two terabytes of tables aimed at cracking A5/1, the most common ciphering algorithm used in GSM. Given 114-bit of known plaintext, we are able to recover the session key with a hit rate of 19%. The tables are expected to be unique as they provide the best coverage yet known to the authors and research workers and they are the first step in a real-world passive attack against GSM. An initial investigation and analysis into the air interface of GSM were performed, from both a theoretical and practical point of view. These …

Internet Of Things: Architecture And Services For Healthcare, Ankita Suvagia Ms.

Dissertations and Theses

Internet of Things (IoT) is a recent prominent collaboration of various technologies that enables spatially distributed devices (“things”) to sense, communicate and share information, thus generating a variety of applications and services in Healthcare. IoT is implemented in multiple domains like Smart city, energy and smart grid, Smart home, weather forecasting, Agriculture, Market and Transportation, Manufacturing and testing industries, Healthcare and many more. IoT serves the purpose of making tasks more efficient and productive and at the same time ensuring quality and reliability. IoT technologies provide an enabling framework for inter-connecting devices, systems, and services that go beyond Machine-to-Machine scenarios …

On The Feasibility Of Utilizing Commercial 4g Lte Systems For Misson-Critical Iot Applications, Alfred Rezk

Dissertations and Theses

Emerging Internet of Things (IoT) applications and services including e-healthcare, intelligent transportation systems, smart grid, and smart homes to smart cities to smart workplace, are poised to become part of every aspect of our daily lives. The IoT will enable billions of sensors, actuators, and smart devices to be interconnected and managed remotely via the Internet. Cellular-based Machine-to-Machine (M2M) communications is one of the key IoT enabling technologies with huge market potential for cellular service providers deploying Long Term Evolution (LTE) networks. There is an emerging consensus that Fourth Generation (4G) and 5G cellular technologies will enable and support these …

Brief Study Of Classification Algorithms In Machine Learning, Ramesh Sankara Subbu

Dissertations and Theses

The purpose of this study is to briefly learn the theory and implementation of three most commonly used Machine Learning algorithms: k-Nearest Neighbors (kNN), Decision Trees and Naïve Bayes. All these algorithms fall under the Classification algorithm category of Unsupervised Machine Learning. This paper is constructed structurally in explaining the working theory behind each algorithm and an implementation of a Machine Learning problem solved by each algorithm. KNN algorithm is designed using Euclidean distance measurement and Decision Trees make use of ID3 algorithm as a basis. We conclude the study by providing an overall picture of its strengths and weaknesses …

Multivalent Rechargeable Batteries, Sudhaprasanna Kumar Padigi

Dissertations and Theses

Li⁺ ion batteries have been the mainstay of high energy storage devices that have revolutionized the operating life time of consumer electronic devices for the past two decades. However, there is a steady increase in demand for energy storage devices with the ability to store more energy and deliver them at high power at low cost, without comprising safety and lifetime.

Li-ion batteries have had significant challenges in increasing the amount of stored energy without affecting the overall lifetime and the ability to deliver stored energy. In order to store and deliver more energy, more lithium ions need to …

Revealing Structural Organization With Liquid Crystal-Based Spectral Imaging Polarimetry, James Campbell Gladish

Dissertations and Theses

Structural organization refers to the particular ordering of scatterers. Probing structural organization by imaging polarized spectral scatter provides insight into the composition of a medium, and can aid in remote sensing, the identification of tissue pathologies, and material characterization and differentiation. The vector nature of polarized light enables it to interact with optical anisotropies within a medium, while the spectral aspect of polarization is sensitive to small-scale structure. However, many polarization studies have limitations, as they provide qualitative image analysis, incomplete anisotropy information, or both. The ability to image the effects of anisotropy and small-scale structure at multiple wavelengths is …

Chemical Reaction Network Control Systems For Agent-Based Foraging Tasks, Joshua Stephen Moles

Dissertations and Theses

Chemical reaction networks are an unconventional computing medium that could benefit from the ability to form basic control systems. In this work, we demonstrate the functionality of a chemical control system by evaluating classic genetic algorithm problems: Koza's Santa Fe trail, Jefferson's John Muir trail, and three Santa Fe trail segments. Both Jefferson and Koza found that memory, such as a recurrent neural network or memories in a genetic program, are required to solve the task. Our approach presents the first instance of a chemical system acting as a control system. We propose a delay line connected with an artificial …

Detection Of Variable Retention Time In Dram, Neraj Kumar

Dissertations and Theses

This thesis investigates a test method to detect the presence of Variable Retention Time (VRT) bits in manufactured DRAM. The VRT bits retention time is modeled as a 2-state random telegraph process that includes miscorrelation between test and use. The VRT defect is particularly sensitive to test and use conditions. A new test method is proposed to screen the VRT bits by simulating the use conditions during manufacturing test. Evaluation of the proposed test method required a bit-level VRT model to be parameterized as a function of temperature and voltage conditions. The complete 2-state VRT bit model combines models for …

Solar Data Analysis, Mike C. T. Ray

Dissertations and Theses

The solar industry has grown considerably in the last few years. This larger scale has introduced more problems as well as possibilities. One of those possibilities is analyzing the data coming from the sites that are now being monitored, and using the information to answer a variety of questions.

We have four questions which are of prime importance identified in this thesis:

1. Can data from customers be trusted?

2. Can we use data from existing sites to determine which sites need the most improvement?

3. Can we implement a location-based algorithm to reduce the amount of false positives for …

A Parabolic Equation Analysis Of The Underwater Noise Radiated By Impact Pile Driving, Nathan Laws

Dissertations and Theses

Impact pile driving can produce extremely high underwater sound levels, which are of increasing environmental concern due to their deleterious effects on marine wildlife. Prediction of underwater sound levels is important to the assessment and mitigation of the environmental impacts caused by pile driving. Current prediction methods are limited and do not account for the dynamic pile driving source, inhomogeneities in bathymetry and sediment, or physics-based sound wave propagation.

In this thesis, a computational model is presented that analyzes and predicts the underwater noise radiated by pile driving and is suitable for shallow, inhomogeneous environments and long propagation ranges. The …

Computer Aided Design Of Permutation, Linear, And Affine-Linear Reversible Circuits In The General And Linear Nearest-Neighbor Models, Ben Schaeffer

Dissertations and Theses

With the probable end of Moore's Law in the near future, and with advances in nanotechnology, new forms of computing are likely to become available. Reversible computing is one of these possible future technologies, and it employs reversible circuits. Reversible circuits in a classical form have the potential for lower power consumption than existing technology, and in a quantum form permit new types of encryption and computation.

One fundamental challenge in synthesizing the most general type of reversible circuit is that the storage space for fully specifying input-output descriptions becomes exponentially large as the number of inputs increases linearly. Certain …

Methods For Efficient Synthesis Of Large Reversible Binary And Ternary Quantum Circuits And Applications Of Linear Nearest Neighbor Model, Maher Mofeid Hawash

Dissertations and Theses

This dissertation describes the development of automated synthesis algorithms that construct reversible quantum circuits for reversible functions with large number of variables. Specifically, the research area is focused on reversible, permutative and fully specified binary and ternary specifications and the applicability of the resulting circuit to the physical limitations of existing quantum technologies.

Automated synthesis of arbitrary reversible specifications is an NP hard, multiobjective optimization problem, where 1) the amount of time and computational resources required to synthesize the specification, 2) the number of primitive quantum gates in the resulting circuit (quantum cost), and 3) the number of ancillary qubits …

A Survey Of Systems For Predicting Stock Market Movements, Combining Market Indicators And Machine Learning Classifiers, Jeffrey Allan Caley

Dissertations and Theses

In this work, we propose and investigate a series of methods to predict stock market movements. These methods use stock market technical and macroeconomic indicators as inputs into different machine learning classifiers. The objective is to survey existing domain knowledge, and combine multiple techniques into one method to predict daily market movements for stocks. Approaches using nearest neighbor classification, support vector machine classification, K-means classification, principal component analysis and genetic algorithms for feature reduction and redefining the classification rule were explored. Ten stocks, 9 companies and 1 index, were used to evaluate each iteration of the trading method. The classification …

Joint Angle Tracking With Inertial Sensors, Mahmoud Ahmed El-Gohary

Dissertations and Theses

The need to characterize normal and pathological human movement has consistently driven researchers to develop new tracking devices and to improve movement analysis systems. Movement has traditionally been captured by either optical, magnetic, mechanical, structured light, or acoustic systems. All of these systems have inherent limitations. Optical systems are costly, require fixed cameras in a controlled environment, and suffer from problems of occlusion. Similarly, acoustic and structured light systems suffer from the occlusion problem. Magnetic and radio frequency systems suffer from electromagnetic disturbances, noise and multipath problems. Mechanical systems have physical constraints that limit the natural body movement. Recently, the …

Material Characterization Of Zinc Oxide In Bulk And Nanowire Form At Terahertz Frequencies, Forest Emerson Kernan

Dissertations and Theses

Many new applications are being proposed and developed for use in the terahertz (THz) frequency region. Similarly, many new materials are being characterized for possible use in this area. Nanostructured forms are of particular interest since they may yield desirable properties, but they remain especially challenging to characterize. This work focuses on the characterization of zinc oxide (ZnO) in bulk and nanowire form. A method for characterizing nanostructures at THz by use of a parallel-plate waveguide (PPWG) is presented. This method is novel in that it is simple, both in theory and practice, and does not require the use of …

Evolved Design Of A Nonlinear Proportional Integral Derivative (Npid) Controller, Shubham Chopra

Dissertations and Theses

This research presents a solution to the problem of tuning a PID controller for a nonlinear system. Many systems in industrial applications use a PID controller to control a plant or the process. Conventional PID controllers work in linear systems but are less effective when the plant or the process is nonlinear because PID controllers cannot adapt the gain parameters as needed. In this research we design a Nonlinear PID (NPID) controller using a fuzzy logic system based on the Mamdani type Fuzzy Inference System to control three different DC motor systems. This fuzzy system is responsible for adapting the …

Optimal Block Encoding And Optimal Entropy For Lossless Image Compression, Larry Ray Dennis

Dissertations and Theses

In this thesis, a novel approach is designed using a quad-tree stack structure to encode the image to determine the optimal block size at the optimal and effective entropy in the lossless image compression method. Proof is given through encoding of the predictor and randomly constructed planes. There is a high degree of relationship between the placement of bits in the planes. Clearly results shows that use of the optimal entropy and encoding block sizes will increase the compression ratio using the lossless method. The cost of using the block size methods to encoding and entropy is discussed and proven. …

A Simplified Approach To Reduce Blocking And Ringing Artifacts In Transform-Coded Images, Jianping Hu

Dissertations and Theses

Presently Block-based Discrete Cosine Transform (BDCT) image coding techniques are widely used in image and video compression applications such as JPEG and MPEG. At a moderate bit rate, BDCT is usually a quite satisfactory solution to most of practical coding applications. However, for high rate compression it produces noticeable blocking and ringing artifacts in the decompressed image. It has been an active research area for a decade for reducing these artifacts. In this thesis, a novel post-processing algorithm is proposed to remove the blocking and ringing artifacts at low bit rate. It is non-iterative and uses both spatial and transform …