Matching Items (27)
Description
The goal of this research was to study the effect of dilution on ammonium and potassium removal from real hydrolyzed urine. The performance of two natural zeolites, clinoptilolite and chabazite, was studied and compared with the help of batch equilibrium experiments at four dilution levels: 100%, 10%, 1% and 0.1% (urine volume/total solution volume). Further, the sorption behavior of other exchangeable ions (sodium, calcium and magnesium) in clinoptilolite and chabazite was studied to improve the understanding of ion exchange stoichiometry. Ammonium and potassium removal were highest at undiluted level in samples treated with clinoptilolite. This is a key finding as it illustrates the benefit of urine source separation. Chabazite treated samples showed highest ammonium and potassium removal at undiluted level at lower doses. At higher doses, potassium removal was similar in undiluted and 10% urine solutions whereas ammonium removal was the highest in 10% urine solutions. In general, chabazite showed higher ammonium and potassium removal than clinoptilolite. The result showed that ion exchange was stoichiometric in solutions with higher urine volumes.
ContributorsRegmi, Urusha (Author) / Boyer, Treavor H (Thesis advisor) / Delgado, Anca G (Committee member) / Hamilton, Kerry (Committee member) / Arizona State University (Publisher)
Created2019
Description
Blockchain scalability is one of the issues that concerns its current adopters. The current popular blockchains have initially been designed with imperfections that in- troduce fundamental bottlenecks which limit their ability to have a higher throughput and a lower latency.
One of the major bottlenecks for existing blockchain technologies is fast block propagation. A faster block propagation enables a miner to reach a majority of the network within a time constraint and therefore leading to a lower orphan rate and better profitability. In order to attain a throughput that could compete with the current state of the art transaction processing, while also keeping the block intervals same as today, a 24.3 Gigabyte block will be required every 10 minutes with an average transaction size of 500 bytes, which translates to 48600000 transactions every 10 minutes or about 81000 transactions per second.
In order to synchronize such large blocks faster across the network while maintain- ing consensus by keeping the orphan rate below 50%, the thesis proposes to aggregate partial block data from multiple nodes using digital fountain codes. The advantages of using a fountain code is that all connected peers can send part of data in an encoded form. When the receiving peer has enough data, it then decodes the information to reconstruct the block. Along with them sending only part information, the data can be relayed over UDP, instead of TCP, improving upon the speed of propagation in the current blockchains. Fountain codes applied in this research are Raptor codes, which allow construction of infinite decoding symbols. The research, when applied to blockchains, increases success rate of block delivery on decode failures.
One of the major bottlenecks for existing blockchain technologies is fast block propagation. A faster block propagation enables a miner to reach a majority of the network within a time constraint and therefore leading to a lower orphan rate and better profitability. In order to attain a throughput that could compete with the current state of the art transaction processing, while also keeping the block intervals same as today, a 24.3 Gigabyte block will be required every 10 minutes with an average transaction size of 500 bytes, which translates to 48600000 transactions every 10 minutes or about 81000 transactions per second.
In order to synchronize such large blocks faster across the network while maintain- ing consensus by keeping the orphan rate below 50%, the thesis proposes to aggregate partial block data from multiple nodes using digital fountain codes. The advantages of using a fountain code is that all connected peers can send part of data in an encoded form. When the receiving peer has enough data, it then decodes the information to reconstruct the block. Along with them sending only part information, the data can be relayed over UDP, instead of TCP, improving upon the speed of propagation in the current blockchains. Fountain codes applied in this research are Raptor codes, which allow construction of infinite decoding symbols. The research, when applied to blockchains, increases success rate of block delivery on decode failures.
ContributorsChawla, Nakul (Author) / Boscovic, Dragan (Thesis advisor) / Candan, Kasim S (Thesis advisor) / Zhao, Ming (Committee member) / Arizona State University (Publisher)
Created2018
Description
As we already know, fresh water is essential to human life as it sustains and replenishes our bodies. Water sustainability is clearly an important issue that need to be addressed in our world of growing demand and shrinking resources. The ASU Future H2O program seeks to make a difference in the development of water sustainability programs by performing experiments that convert urine into reusable water. The goal is to make reusable water processes become inexpensive and easily accessible to local businesses. This promises a significant environmental impact. In order to make the process of development more efficient we can combine engineering technology with scientific experimentation. As an engineering student and an advocate of water sustainability, I have a chance to design the front-end platform that will use IoT to make the experimental process more accessible and effective. In this paper, I will document the entire process involved in the designing process and what I have learned.
ContributorsTran, Phung Thien (Author) / Boscovic, Dragan (Thesis director) / Boyer, Treavor (Committee member) / School of Earth and Space Exploration (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Through my work with the Arizona State University Blockchain Research Lab (BRL) and JennyCo, one of the first Healthcare Information (HCI) HIPAA - compliant decentralized exchanges, I have had the opportunity to explore a unique cross-section of some of the most up and coming DLTs including both DAGs and blockchains. During this research, four major technologies (including JennyCo’s own systems) presented themselves as prime candidates for the comparative analysis of two models for implementing JennyCo’s system architecture for the monetization of healthcare information exchanges (HIEs). These four identified technologies and their underlying mechanisms will be explored thoroughly throughout the course of this paper and are listed with brief definitions as follows: Polygon - “Polygon is a “layer two” or “sidechain” scaling solution that runs alongside the Ethereum blockchain. MATIC is the network’s native cryptocurrency, which is used for fees, staking, and more” [8]. Polygon is the scalable layer involved in the L2SP architecture. Ethereum - “Ethereum is a decentralized blockchain platform that establishes a peer-to-peer network that securely executes and verifies application code, called smart contracts.” [9] This foundational Layer-1 runs thousands of nodes and creates a unique decentralized ecosystem governed by turing complete automated programs. Ethereum is the foundational Layer involved in the L2SP. Constellation - A novel Layer-0 data-centric peer-to-peer network that utilizes the “Hypergraph Transfer Protocol or HGTP, a DLT known as a [DAG] protocol with a novel reputation-based consensus model called Proof of Reputable Observation (PRO). Hypergraph is a feeless decentralized network that supports the transfer of $DAG cryptocurrency.” [10] JennyCo Protocol - Acts as a HIPAA compliant decentralized HIE by allowing consumers, big businesses, and brands to access and exchange user health data on a secure, interoperable, and accessible platform via DLT. The JennyCo Protocol implements utility tokens to reward buyers and sellers for exchanging data. Its protocol nature comes from its DLT implementation which governs the functioning of on-chain actions (e.g. smart contracts). In this case, these actions consist of secure and transparent health data exchange and monetization to reconstitute data ownership to those who generate that data [11]. With the direct experience of working closely with multiple companies behind the technologies listed, I have been exposed to the benefits and deficits of each of these technologies and their corresponding approaches. In this paper, I will use my experience with these technologies and their frameworks to explore two distributed ledger architecture protocols in order to determine the more effective model for implementing JennycCo’s health data exchange. I will begin this paper with an exploration of blockchain and directed acyclic graph (DAG) technologies to better understand their innate architectures and features. I will then move to an in-depth look at layered protocols, and healthcare data in the form of EHRs. Additionally, I will address the main challenges EHRs and HIEs face to present a deeper understanding of the challenges JennyCo is attempting to address. Finally, I will demonstrate my hypothesis: the Hypergraph Transfer Protocol (HGTP) model by Constellation presents significant advantages in scalability, interoperability, and external data security over the Layer-2 Scalability Protocol (L2SP) used by Polygon and Ethereum in implementing the JennyCo protocol. This will be done through a thorough breakdown of each protocol along with an analysis of relevant criteria including but not limited to: security, interoperability, and scalability. In doing so, I hope to determine the best framework for running JennyCo’s HIE Protocol.
ContributorsVan Bussum, Alexander (Author) / Boscovic, Dragan (Thesis director) / Grando, Adela (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
Potentiometric instrumentation technologies are widely used across many disciplines of science and engineering providing the ability to measure changes to specific environmental variables through various types of sensor electrodes and selective membranes. However, types I, II, and III potentiometric sensor electrodes are limited by biofouling activity, membrane maintenance, grounding sensitivity, thermodynamic variables, and electromagnetic interference. Further, algorithms embedded into instrumentation hardware have impeded the usefulness of such measurements outside of highly controlled environments. Reliability of accurate measurement using these types of senor electrodes is limited to industrial and lab applications in chemistry and nominally active biological environments. Novel innovations in using exotic materials have improved the usefulness of Type II (e.g. tantalum-rubidium-doped titanium) and Type III (e.g. Nafion™ membranes) sensor electrodes, but those sensors are still limited to measuring a single selective parameter. This scope of work investigates utilizing a novel non-selective membrane, or naturally occurring biofilm membrane, as the active sensing surface of a graphite electrode as a new Type IV potentiometric sensor electrode (e.g., the MiProbE™) in biologically active environments. The analysis herein demonstrates decomposition of these non-selective signals into real-time metabolic activity, measurement of key biochemical processes and environmental condition parameters through classical mathematical analysis methods providing the basis of Potentiomics – the characterization and quantification of biochemical metabolic processes in highly dynamic non-equilibrium states.
ContributorsTaylor, Evan (Author) / Weiss, Taylor L (Thesis advisor) / Brown, Albert F (Committee member) / Boyer, Treavor H (Committee member) / Arizona State University (Publisher)
Created2022
Description
Cryptographic voting systems such as Helios rely heavily on a trusted party to maintain privacy or verifiability. This tradeoff can be done away with by using distributed substitutes for the components that need a trusted party. By replacing the encryption, shuffle, and decryption steps described by Helios with the Pedersen threshold encryption and Neff shuffle, it is possible to obtain a distributed voting system which achieves both privacy and verifiability without trusting any of the contributors. This thesis seeks to examine existing approaches to this problem, and their shortcomings. It provides empirical metrics for comparing different working solutions in detail.
ContributorsBouck, Spencer Joseph (Author) / Bazzi, Rida (Thesis advisor) / Boscovic, Dragan (Committee member) / Shoshitaishvili, Yan (Committee member) / Arizona State University (Publisher)
Created2021
Description
Bitcoin (BTC) shares many characteristics with traditional stocks, but it is much more volatile since the cryptocurrency market is unregulated. The high volatility makes BTC a very high risk-high reward investment and predictive analysis can be very useful to obtain good returns and minimize risk. Taking Cocco et al. [1] as the primary reference, this thesis tries to reproduce their findings by building two BTC price forecasting models, Long Short-Term Memory (LSTM) and Bayesian Neural Network (BNN), and finding that the Mean Absolute Percentage Error (MAPE) is lower for the initial BNN model in comparison to the initial LSTM model. In addition to forecasting the value of BTC, a metric called trend% is developed to gauge the models’ ability to capture the trend of how the price varies from one timestep to the next and used to compare the trend prediction performance. It is found that both initial models make random predictions for the trend. Improvements like removing the stochastic component from the data and forecasting returns as opposed to price values show that both models show comparable performance in terms of both MAPE and trend%. The thesis concludes by discussing the future work that can be done to potentially improve the above models. One of the possibilities mentioned is to use on-chain data from the BTC blockchain coupled with the real-world knowledge of BTC exchanges and feed this as input features to the models.
ContributorsMittal, Shivansh (Author) / Boscovic, Dragan (Thesis advisor) / Davulcu, Hasan (Committee member) / Candan, Kasim (Committee member) / Arizona State University (Publisher)
Created2022
Description
The main objective of this work is to study novel stochastic modeling applications to cybersecurity aspects across three dimensions: Loss, attack, and detection. First, motivated by recent spatial stochastic models with cyber insurance applications, the first and second moments of the size of a typical cluster of bond percolation on finite graphs are studied. More precisely, having a finite graph where edges are independently open with the same probability $p$ and a vertex $x$ chosen uniformly at random, the goal is to find the first and second moments of the number of vertices in the cluster of open edges containing $x$. Exact expressions for the first and second moments of the size distribution of a bond percolation cluster on essential building blocks of hybrid graphs: the ring, the path, the random star, and regular graphs are derived. Upper bounds for the moments are obtained by using a coupling argument to compare the percolation model with branching processes when the graph is the random rooted tree with a given offspring distribution and a given finite radius. Second, the Petri Net modeling framework for performance analysis is well established; extensions provide enough flexibility to examine the behavior of a permissioned blockchain platform in the context of an ongoing cyberattack via simulation. The relationship between system performance and cyberattack configuration is analyzed. The simulations vary the blockchain's parameters and network structure, revealing the factors that contribute positively or negatively to a Sybil attack through the performance impact of the system. Lastly, the denoising diffusion probabilistic models (DDPM) ability for synthetic tabular data augmentation is studied. DDPMs surpass generative adversarial networks in improving computer vision classification tasks and image generation, for example, stable diffusion. Recent research and open-source implementations point to a strong quality of synthetic tabular data generation for classification and regression tasks. Unfortunately, the present state of literature concerning tabular data augmentation with DDPM for classification is lacking. Further, cyber datasets commonly have highly unbalanced distributions complicating training. Synthetic tabular data augmentation is investigated with cyber datasets and performance of well-known metrics in machine learning classification tasks improve with augmentation and balancing.
ContributorsLa Salle, Axel (Author) / Lanchier, Nicolas (Thesis advisor) / Jevtic, Petar (Thesis advisor) / Motsch, Sebastien (Committee member) / Boscovic, Dragan (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2023
Description
Hydrophobic ionizable organic compounds (HIOCs) like per- and polyfluoroalkyl substances (PFAS), certain pharmaceuticals, and surfactants have been detected in groundwater, wastewater, and drinking water. Anion exchange resin treatment is an effective process for removal of anionic contaminants from water. Spent anion exchange resins are conventionally regenerated with high alcohol by volume (ABV) methanol in solution with brine. While effective for regeneration of resins saturated with inorganic anions such as sulfate, nitrate, and perchlorate, HIOCs prove more resistant to regeneration. This research investigated the efficacy of using novel cosolvent solutions with brine to regenerate resins saturated with organic carboxylate and sulfonate anions to understand the effects cosolvent properties have on regenerative ability. Experiments were conducted on six PFAS compounds to evaluate trends in regeneration for three alcohols. For all PFAS species, equivalent ABV and brine solutions showed greatest regeneration with 1-propanol over ethanol and methanol. Experiments with the pharmaceutical sodium diclofenac were conducted showing similar regeneration of 75% methanol and 25% 1-propanol for equivalent salt concentrations and higher regeneration with 1-propanol than ethanol and methanol for equivalent ABV. A series of experiments with surfactant dodecylbenzene sulfonate determined that the key parameters to determine regeneration of the resin for an alcohol cosolvent solution were cosolvent volume fraction, molar mass, Kow value, solution ionic strength, and dielectric constant. Individual assessments on the cost-effectiveness, flammability, and sustainability of cosolvent solutions point to possible future experiments and opportunities for recycled distillery waste streams as regenerative solutions for anion exchange resin.
ContributorsGraham, Cole David (Author) / Boyer, Treavor H (Thesis advisor) / Conroy-Ben, Otakuye (Committee member) / Garcia Segura, Sergio (Committee member) / Arizona State University (Publisher)
Created2022
Description
Blockchain technology enables peer-to-peer transactions through the elimination of the need for a centralized entity governing consensus. Rather than having a centralized database, the data is distributed across multiple computers which enables crash fault tolerance as well as makes the system difficult to tamper with due to a distributed consensus algorithm.
In this research, the potential of blockchain technology to manage energy transactions is examined. The energy production landscape is being reshaped by distributed energy resources (DERs): photo-voltaic panels, electric vehicles, smart appliances, and battery storage. Distributed energy sources such as microgrids, household solar installations, community solar installations, and plug-in hybrid vehicles enable energy consumers to act as providers of energy themselves, hence acting as 'prosumers' of energy.
Blockchain Technology facilitates managing the transactions between involved prosumers using 'Smart Contracts' by tokenizing energy into assets. Better utilization of grid assets lowers costs and also presents the opportunity to buy energy at a reasonable price while staying connected with the utility company. This technology acts as a backbone for 2 models applicable to transactional energy marketplace viz. 'Real-Time Energy Marketplace' and 'Energy Futures'. In the first model, the prosumers are given a choice to bid for a price for energy within a stipulated period of time, while the Utility Company acts as an operating entity. In the second model, the marketplace is more liberal, where the utility company is not involved as an operator. The Utility company facilitates infrastructure and manages accounts for all users, but does not endorse or govern transactions related to energy bidding. These smart contracts are not time bounded and can be suspended by the utility during periods of network instability.
In this research, the potential of blockchain technology to manage energy transactions is examined. The energy production landscape is being reshaped by distributed energy resources (DERs): photo-voltaic panels, electric vehicles, smart appliances, and battery storage. Distributed energy sources such as microgrids, household solar installations, community solar installations, and plug-in hybrid vehicles enable energy consumers to act as providers of energy themselves, hence acting as 'prosumers' of energy.
Blockchain Technology facilitates managing the transactions between involved prosumers using 'Smart Contracts' by tokenizing energy into assets. Better utilization of grid assets lowers costs and also presents the opportunity to buy energy at a reasonable price while staying connected with the utility company. This technology acts as a backbone for 2 models applicable to transactional energy marketplace viz. 'Real-Time Energy Marketplace' and 'Energy Futures'. In the first model, the prosumers are given a choice to bid for a price for energy within a stipulated period of time, while the Utility Company acts as an operating entity. In the second model, the marketplace is more liberal, where the utility company is not involved as an operator. The Utility company facilitates infrastructure and manages accounts for all users, but does not endorse or govern transactions related to energy bidding. These smart contracts are not time bounded and can be suspended by the utility during periods of network instability.
ContributorsSadaye, Raj Anil (Author) / Candan, Kasim S (Thesis advisor) / Boscovic, Dragan (Committee member) / Zhao, Ming (Committee member) / Arizona State University (Publisher)
Created2019