21793 research outputs found
Sort by
Hydrodynamic and Water-quality Simulation of a Eutrophic Lake
Get PDFEutrophication is the over-enrichment of nutrients. It has become a leading cause of lake pollution. The gathering of nutrients in lakes is influenced by human activities, including the disposal of domestic wastewater and other waste effluents. This introduces an overabundant nutrient loading into lakes and intensifies eutrophication. In a eutrophic lake, species diversity decreases, dissolved oxygen contents deplete, and aquatic animals and plants die out, eventually leading to an ecosystem collapse. The purpose of this study is to improve our understanding of the impacts of domestic wastewater disposal on lake water quality. This study takes the approach of numerical simulations to predict the transport, diffusion, and degradation of water pollutants in a lake. The simulations are performed using the Environmental Fluid Dynamic Code (EFDC). The site of study is Lake Caron in Quebec, where periodic eutrophication occurs due to the discharge of untreated sewage. The scope of work includes an analysis of the responses of the lake water to the nutrient loading. The simulations consider seven parameters, including chlorophyll a, dissolved oxygen, chemical oxygen demand, carbonaceous biochemical oxygen demand, nitrate nitrogen, ammonia nitrogen and total phosphorus. The results capture hydrodynamics and water quality processes in Lake Caron. The results show spatial and temporal variations in the concentrations of pollutants, suggesting that the nutrient-rich wastewater can trigger nuisance algal blooms and deteriorating water quality. This study demonstrates the efficiency and effectiveness of the EFDC model. The simulation methods from this study can be applied to other lakes for the investigation of eutrophication
holy foolery as salvation in the russian orthodox church
Get PDFThis paper seeks to explore the various interconnected theological aspects present in the Eastern Orthodox phenomenon known as the holy fool by bridging 2 notions; feigned madness and salvation. It will begin by addressing the inception, and scriptural origin of holy foolery. Moving from presenting the definitions and ideologies from a rather widespread perspective, this research will come to focus on the holy fools of Russia, attempting to address the factors which have contributed to the strength and duration of the presence of holy fools in Russia over the centuries; far outlasting that of other Eastern Churches, and impacting its theological, socio-cultural, and literary history. In analyzing this phenomenon particularly within the Russian context, it is essential to address notions of Russian mysticism and several central ideologies of theologian Vladimir Lossky. Within this discussion, the concepts of salvation and deification will emerge. Ultimately, the goal will be to assess the ways and reasons for the unicity and duration of the holy fools’ existence in Russia and to convey the deeply rooted connection between this practice and the Eastern Orthodox understanding of theōsis as salvation
Inter-Contrast and Inter-Modal Medical Image Registrations: From Traditional Energy-Based to Deep Learning Methods
Get PDFImage registration is a crucial step in many medical image processing pipelines. The process aligns images of the same tissue taken at different times or with different imaging modalities. The first focus of this thesis is on the registration of ultrasound (US) images, which are low-cost, portable, safe, real-time, and commonly employed in several image-guided operations. Image registration of intraoperative US with preoperative images is required in image-guided surgeries. Computed Tomography (CT) scans and Magnetic Resonance Imaging (MRI) generally visualize the bones and soft tissues with better spatial details than US. Therefore, surgeons and interventionalists prefer them to US for the preoperative planning. These preoperative images should be registered to the intraoperative US images in image-guided interventions, which is a challenging task and an open area of research. Beyond image-guided interventions, image registration is a critical step in several other medical image analysis pipelines. The second focus of this work is on inter-contrast CT and MRI registrations. MRI is the primary modality for diagnosing neurodegenerative diseases such as Alzheimer's Disease. MRI comes with various contrasts, and the fusion of these contrasts taken at different times or from many subjects can give clinicians valuable information. However, MRI has a longer waiting time and less availability than CT. Thus, designing inter-modal image registration techniques to align MRI data with CT scans is essential in medical image analysis. Novel methods to tackle this problem are proposed in this thesis. The traditional image registration methods, which solve an optimization problem iteratively, can be time-inefficient for analyzing large datasets. Image registration using Deep Learning (DL) can accelerate the process but usually require training data. In this thesis, several novel methods for performing inter-contrast image registration are proposed in Chapters 3 to 5. These methods span both energy- and DL-based techniques with DL-based methods being more computationally efficient. We conclude the thesis in Chapter 6 by providing possible future research directions
The Self-Writing Encyclopedia UI Design for Emergent Story Discovery
Get PDFOne of the main appeals of emergent narrative games is the stories they can generate. However, these games tend to be complex simulations, resulting in a large amount of information that makes the discoverability of narratives challenging. To alleviate this problem, we believe redesigning the user interface and experience can facilitate the discovery process of stories. But what kind of interface could help even inexperienced players navigate easily such a large mass of information?
The answer we are looking for might be in web design, more specifically, Wikipedia and web browsers. This research tested two interfaces' iterations of a game. Participants with varying experiences with emergent narratives had to play with one of the interfaces and share their feedback on their experience during a recorded interview. The feedback collected on the first test helped redesign the second interface's iteration, while the feedback collected during the second test helped determine if the research was going in the right direction.
According to participants, the first interface's iteration was unsuitable for sifting through a large amount of information. However, the second interface's iteration, which had a design much more similar to websites, proved to be well received by participants. Because of these findings, we believe that web design might be a solution to solve the discoverability problems of stories in emergent narrative games.
Although the results point in a promising direction, a larger audience needs to play with the second interface to confirm that it is, in fact, approachable for a majority of players. Secondly, to adequately evaluate the effectiveness of the interface for facilitating the discovery of stories, we need a research method that can prove when players find a narrative in a quantifiable way and use this method with the second interface
Wind loading on a stepped roof building: comparison of field measurements, wind tunnel data, and standard provisions
Get PDFThis study investigates wind loads on stepped roof buildings measured in the field and in an atmospheric boundary layer wind tunnel to verify the suitability of the North American codes and standards for the design of stepped roofs. Good agreement has been generally found between field and wind tunnel results. The field measurements and wind tunnel results were compared with the NBCC 2020 and ASCE 7-22 provisions. It was found that the Edge provisions of NBCC 2020 are currently underestimated and need to be increased. The study suggests merging the Corner and Edge zones into a single “Perimeter” zone in NBCC 2020 as this would resolve the current underestimation of the NBCC Edge wind loads and add simplicity to the Code provisions. Peaks of ASCE 7-22 were found conservative, except for the zone near the step wall on the lower roof; ASCE 7-22 positive peaks seem to be underestimated
API Finder: Accurate Extraction of Method Binding Information from Call Sites without Building the Code
Get PDFResearchers and practitioners have introduced many static analysis tools to enhance the quality of software. Several tools (e.g.,WALA) are highly effective and based on mature compilers. However, all of these tools usually require a complete codebase to compile the project under analysis. In many scenarios, academics and practitioners need to analyze partial programs collected from the web or online source code repositories. A partial program is a subset of the complete codebase. The compiler requires a complete codebase to resolve all binding information to identify type information of program elements (e.g., the return type and the argument types of method invocation, type of field instance), and as a result, most of the static analysis tools cannot extract type information for program elements in partial programs.
In this paper, we introduce API Finder, a tool that can accurately extract method binding information from method references (i.e., call sites) in partial programs. Our approach requires only the Java version of the project, the dependent external library artifacts, and the method invocation as inputs in order to generate precise method-binding information. We also provide support for extracting the Java version of the project, as well as dependent external library artifacts for the Gradle and Maven build systems. We evaluated the accuracy of the method-binding information generated by our tool with the Eclipse JDT (Java Development Tool) Compiler across eleven complete projects. Our tool has an accuracy rate ranging between 93% to 99% in our evaluated projects. Our tool also has an average response time of 381 milliseconds for any method-binding information extraction. In addition, as an application of our tool, we have implemented a Chrome browser extension for displaying the method signature upon clicking on any method reference for the GitHub platform
Multidisciplinary Optimization of Shoe Midsole Structures using Tetrahedral Mesh Generation and Swarm Intelligence
Get PDFCreating functional midsoles for shoes is a challenging task that involves considering different aspects such as stability, comfort, manufacturability, and aesthetics. No single approach exists to design a midsole that meets all these objectives effectively. Therefore, this study aims to introduce a multidisciplinary optimization method to develop custom shoe midsole structures. The proposed approach involves utilizing tetrahedral mesh generation to generate diverse structures and leveraging swarm intelligence to search for optimal designs. Tetrahedral mesh generation is used to create midsole structures because tetrahedral structures are renowned for their exceptional strength. Additionally, tetrahedral mesh generation is a well-established tool that provides the added advantage of fully automatic construction for complex shaped midsoles. By adjusting the mesh generation parameters, a wide range of solutions can be generated that meet multiple objectives. To enhance the swarm’s exploration of the design space and discover more local optima, a new swarm behavior is developed that promotes diversity. Furthermore, a quantitative measurement tool is created to evaluate various objectives. In order to test the effectiveness of the generative approach, the midsoles obtained from the design exploration are analyzed that performed the best and the worst in relation to each objective. The findings revealed a substantial difference between them, with scores differing by two to four times. Additionally, when compared to other lattice structures, the tetrahedral midsole structure created by the proposed method demonstrated superior compliance with the foot and better redistribution of plantar stress. This makes it an ideal candidate for use in shoe midsoles. The multidisciplinary optimization technique proposed here is a valuable resource for engineers and designers in the footwear industry, allowing them to develop high-performance midsole structures that meet the needs
of both consumers and athletes. Furthermore, this method can be applied to optimize other complex structures in various industries, such as civil, automotive, and aerospace engineerin
Exploring the Properties of Synthetic Gene Oscillators in Single Bacteria Cells
Get PDFNatural oscillators exhibit remarkable precision in their period while being robust to environmental changes. While many synthetic gene circuits have already been engineered to achieve various functions, many exhibit unreliable and unpredicted behaviors. In this project, we aim to engineer precise genetic oscillators and to characterize the relationship between period and precision. Using mutagenesis, we have generated large libraries of different circuit variants with the key regulatory regions of the circuit mutated to observe a wide range of dynamics. We focus on two different circuit architectures, the repressilator and the dual feedback oscillator. Modelling of both circuits has shown that there are distinct trends in circuit parameters that are necessary to achieve the highest precision. In order to accurately characterize these circuit dynamics at the single-cell level, we employ a microfluidic device called the mother machine. We show these trade-offs are present in the circuit libraries, specifically between the period length and precision for both the repressilator and dual-feedback oscillator circuits. We also employ a mutagenesis method to generate novel oscillators with increased precision. By building such circuit libraries and characterizing the different dynamics we aim to gain a deeper understanding of the design principles of natural oscillators, while providing a tool with potential biotechnology applications
On Parallelization of Categorical Data Clustering
Get PDFWe study parallelization of categorical data clustering algorithms in an MPI platform. Clustering such data has been a daunting task even for sequential algorithms, mainly due to the challenges in finding suitable similarity/distance measures. We propose a parallel version of the k-modes algorithm, called PV3, which maintains the same clustering quality as produced by the sequential approach while achieving reasonable speed-ups. PV3 is programmed to ensure deterministic processing in a parallel environment. To produce better clustering results, we then develop an initialization method called Revised Density Method (RDM) based on the notion of density. Additionally, we develop variants of the RDM method to further enhance its performance. we then study effective ways to parallelize RDM and its variants. To further exploit parallelism opportunities, we develop an Ensemble Parallelizing Process (EPP) framework. This framework can be used with any desired initialization/clustering algorithms with different levels of parallelism. Using our different RDM initialization techniques along with the PV3 algorithm in the EPP framework, we then build an RDM realization of EPP, called RDM EPP. The result of our numerous experiments using benchmark categorical datasets indicate the quality metric of RDM EPP to be among the top three sequential k-modes based clustering algorithms. In terms of speed up, the results indicate to be 7 times faster for some datasets, though much larger datasets are required for a more comprehensive scalability study of RDM EPP
Effects of Processing Time Distributions and Rescheduling Policies on Efficiency and Instability for Single Machine Settings
Get PDFOperating room (OR) scheduling is becoming increasingly important and poses a challenging problem due to the presence of uncertainty. Motivated by OR scheduling, we study the single machine scheduling problem with uncertainty in both dynamic arrivals and stochastic processing times. We use rescheduling to handle uncertainty and study both efficiency and instability (a measure of schedule deviation). The chosen efficiency metric, final total weighted tardiness (FTWT), is the total weighted tardiness of the final schedule. We develop a discrete-event simulation framework with embedded optimization to conduct two computational experiments. The first experiment analyzes the joint effect of different processing time distributions and rescheduling policies for the single machine scheduling problem with deterministic processing times and dynamic arrivals. Secondly, we analyze the joint effect of different processing time distributions and rescheduling policies for the single machine problem with stochastic processing times and dynamic arrivals. For both experiments, we find that the variance of the processing time distributions has a greater impact than the shape of the distribution. Furthermore, the eventJobCompletion policy, which reschedules every time a job finishes processing, performs well across all distributions in both experiments.
For the stochastic experiment, the eventJobCompletion policy also stood out as being the most consistent across all processing time distributions. Finally, in both experiments, we find that the average length of the rescheduling interval does not have an effect on total instability and FTWT