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The effectiveness of reverse osmosis (RO) membrane systems may be compromised due to fouling, of which biofouling (excessive growth of biomass) is the most troublesome. Effective control of biofouling is essential to improve membrane performance and reduce operating costs. The periodic application of chemical cleaning agents is possibly the most widely practiced method of biofouling control in RO membranes. This research investigated advanced chemical cleaning strategies for biofouling control. The first part of this study concluded that short-term accelerated biofouling studies using lab-scale membrane fouling simulators (MFSs) are a representative and suitable approach for the prediction of long-term biofouling development in membrane systems. Thereon, the superior efficiency of urea as an alternative to conventional chemical cleaning agents was demonstrated (i) at lab-scale using MFSs, (ii) for full-scale industrial spiral-wound membranes and (iii) for multiple cleaning cycles during long-term operation. Periodic chemical cleaning with urea resulted in better restoration of membrane performance, higher biomass inactivation, enhanced biofilm solubilization and removal, disintegration of extracellular polymeric substances (EPS) particularly proteins, and a considerable reduction of key biofilm-forming bacteria. This research presented enhanced chemical cleaning strategies aiming to increase the removal of biofilms, reduce biomass accumulation and its impact on membrane performance, and delay fresh biofilm formation.

Enterprises acquire large amounts of data from a variety of sources with the goal of extracting valuable insights and enabling informed analysis. Unfortunately, organizations continue to be hindered by poor data quality as they wrangle with their data to extract value since most real datasets are rarely error-free. Poor data quality is a pervasive problem that spans across all industries causing unreliable data analysis, and costing billions of dollars. The large body of datasets, the pace of data acquisition, and the heterogeneity of data sources pose challenges towards achieving high-quality data. These challenges are further exacerbated with data privacy and data diversity requirements. In this thesis, we study and propose solutions to address data duplication, managing the trade-off between data cleaning and data privacy, and computing diverse data instances. In the first part of this thesis, we address the data duplication problem. We propose a duplication detection framework, which combines word-embeddings with constraints among attributes to improve the accuracy of deduplication. We propose a set of constraint-based statistical features to capture the semantic relationship among attributes. We showed that our techniques achieve comparative accuracy on real datasets. In the second part of this thesis, we study the problem of data privacy and data cleaning, and we present a Privacy-Aware data Cleaning-As-a-Service (PACAS) framework to protect privacy during the cleaning process. Our evaluation shows that PACAS safeguards semantically related sensitive values, and provides lower repair errors compared to existing privacy-aware cleaning techniques. In the third part of this thesis, we study the problem of finding a diverse anonymized data instance where diversity is measured via a set of diversity constraints, and propose an algorithm to seek a k-anonymous relation with value suppression as well as satisfying given diversity constraints. We conduct extensive experiments using real and synthetic data showing the effectiveness of our techniques, and improvement over existing baselines. / Thesis / Doctor of Philosophy (PhD)

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Geckos can freely climb on walls and ceilings against their body weight at speed of over 1ms-1. Switching between attachment and detachment seem simple and easy for geckos, without considering the surface to be dry or wet, smooth or rough, dirty or clean. In addition, gecko can shed dirt particles during use, keeping the adhesive pads clean. Mimicking this biological system can lead to a new class of dry adhesives for various applications. However, gecko’s unique dry self-cleaning mechanism remains unknown, which impedes the development of self-cleaning dry adhesives. In this dissertation we provide new evidence and self-cleaning mechanism to explain how gecko shed particles and keep its sticky feet clean. First we studied the dynamic enhancement observed between micro-sized particles and substrate under dry and wet conditions. The adhesion force of soft (polystyrene) and hard (SiO2 and Al2O3) micro-particles on soft (polystyrene) and hard (fused silica and sapphire) substrates was measured using an atomic force microscope (AFM) with retraction (z-piezo) speed ranging over 4 orders of magnitude. The adhesion is strongly enhanced by the dynamic effect. When the retraction speeds varies from 0.02 µm/s to 156 µm/s, the adhesion force increases by 10% ~ 50% in dry nitrogen while it increases by 15%~70% in humid air. A dynamic model was developed to explain this dynamic effect, which agrees well with the experimental results. Similar dynamic enhancement was also observed in aqueous solution. The influence of dynamic factors related to the adhesion enhancement, such as particle inertia, viscoelastic deformations and crack propagation, was discussed to understand the dynamic enhancement mechanisms. Although particles show dynamic enhancement, Gecko fabrillar hair shows a totally different trend. The pull off forces of a single gecko seta and spatula was tested by AFM under different pull-off velocities. The result shows that both the spatula and the seta have a rate independent adhesion response in normal retraction, which is quite different from micro-particles. Further research indicated the shape of the contact area was a key factor to the dynamic effect. In order to verify this hypothesis, artificial gecko spatula made of glass fibers was nanofabricated by a focus ion beam (FIB) and tested by AFM. These manmade spatulae also show a rate independent adhesion response. The dynamic adhesion of a single gecko seta and spatula were simulated with finite element analysis and the results also confirm the rate independent phenomena.. In conclusion, self-cleaning is induced by dynamic effect during gecko locomotion. The relative dynamic adhesion change between particles and seta makes it possible for gecko to shed the dirt particles while walking.Finally, the fatigue property of gecko seta was examined with the atomic force microscope under cyclic attachment/detachment process, mimicking gecko running. The adhesion force versus cycles has been tested and evaluated. Fatigue mechanism of gecko seta was also analyzed based on the experimental findings.

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Spreadsheets are routinely used in business and scientific contexts, and one of the most vexing challenges data analysts face is performing data cleaning prior to analysis and evaluation. The ad-hoc and arbitrary nature of data cleaning problems, such as typos, inconsistent formatting, missing values, and a lack of standardization, often creates the need for highly specialized pipelines. We ask whether an LLM can find its way around a spreadsheet and how to support end-users in taking their free-form data processing requests to fruition. Just like RAG retrieves context to answer users' queries, we demonstrate how we can retrieve elements from a code library to compose data processing pipelines. Through comprehensive experiments, we demonstrate the quality of our system and how it is able to continuously augment its vocabulary by saving new codes and pipelines back to the code library for future retrieval. / Master of Science / Spreadsheets are frequently utilized in both business and scientific settings, and one of the most challenging tasks that must be accomplished before analysis and evaluation can take place is the cleansing of the data. The ad-hoc and arbitrary nature of issues in data quality, such as typos, inconsistent formatting, missing values, and lack of standardization, often creates the need for highly specialized data cleaning pipelines. Within the scope of this thesis, we investigate whether a large language model (LLM) can navigate its way around a spreadsheet, as well as how to assist end-users in bringing their free-form data processing requests to fruition. Just like Retrieval-Augmented Generation (RAG) retrieves context to answer user queries, we demonstrate how we can retrieve elements from a Python code reference to compose data processing pipelines. Through comprehensive experiments, we showcase the quality of our system and how it is capable of continuously improving its code-writing ability by saving new codes and pipelines back to the code library for future retrieval.

The objectives of this research were to quantitatively apply food stains to a rayon, a nylon, and an olefin pile upholstery fabric, and to determine the effects of aging times and cleaning agents on their removal. Another objective was to correlate the instrumental color change measurements with ratings obtained from a consumer panel. The specimens were soiled with mustard, vegetable oil, milk, and syrup. After aging for one day or two weeks, the specimens were treated for stain removal with a detergent-vinegar solution, perchloroethylene, isopropyl alcohol, or ammonia water while attached to a simulated chair arm. Soil removal was evaluated by measuring light reflectance and color values on a Hunter Color-Difference Meter®. A consumer panel rated the specimens according to AATCC Stain Release Replicas, and stated whether or not each specimen was acceptable for use in their homes. Statistical analyses indicated the following major conclusions: (1) the fabric and stain variables significantly affected the instrumental values of color change; (2) the variables exhibiting a significant effect on the consumer ratings were fabric, stain, and stain remover; (3) the rayon fabric tended to react the most unfavorably of the three fabrics to the treatment; (4) the milk and mustard stains tended to be the most easily removed, while the oil and the syrup stains were more difficult; and (5) a correlation existed between instrumental values and consumer ratings of color change. / Master of Science

The purpose of this study is to determine sound principles for custodial service in the small school.