Physical Sciences and Mathematics Commons^™

Interactions And Dynamics Of One-Dimensional Droplets, Bubbles And Kinks, Garyfallia Katsimiga, Simeon I. Mistakidis, Boris A. Malomed, Dimitris J. Frantzeskakis, Ricardo Carretero-Gonzalez, Panayotis G. Kevrekidis

Physics Faculty Research & Creative Works

We Explore The Dynamics And Interactions Of Multiple Bright Droplets And Bubbles, As Well As The Interactions Of Kinks With Droplets And With Antikinks, In The Extended One-Dimensional Gross–Pitaevskii Model Including The Lee–Huang–Yang Correction. Existence Regions Are Identified For The One-Dimensional Droplets And Bubbles In Terms Of Their Chemical Potential, Verifying The Stability Of The Droplets And Exposing The Instability Of The Bubbles. The Limiting Case Of The Droplet Family Is A Stable Kink. The Interactions Between Droplets Demonstrate In-Phase (Out-Of-Phase) Attraction (Repulsion), With The So-Called Manton's Method Explicating The Observed Dynamical Response, And Mixed Behavior For Intermediate Values Of …

Hawc Study Of The Very-High-Energy Γ-Ray Spectrum Of Hawc J1844−034, A. Albert, C. Alvarez, D. Avila Rojas, H. A.Ayala Solares, R. Babu, E. Belmont-Moreno, M. Breuhaus, T. Capistrán, A. Carramiñana, S. Casanova, J. Cotzomi, S. Coutiño De León, E. De La Fuente, D. Depaoli, R. Diaz Hernandez, B. L. Dingus, M. A. Duvernois, M. Durocher, K. Engel, C. Espinoza, K. L. Fan, K. Fang, N. Fraija, J. A. Garcia-Gonzalez, M. M. Gonzalez, J. A. Goodman, S. Groetsch, J. P, Harding, I. Herzog, J. Hinton, D. Huang, F. Hueyotl-Zahuantitla, T. B. Humensky, P. Huntemeyer, V. Joshi, S. Kaufmann, J. Lee, H. Leon Vargas, A. L. Longinotti, G. Luis-Raya, K. Malone, O. Martinez, J. Martinez-Castro, J. A. Matthews, P. Miranda-Romagnoli, J. A. Morales-Soto, E. Moreno, M. Mostafa, L. Nellen, R. Noriega-Papaqui, L. Olivera-Nieto, N. Omodei, E. G. Perez-Perez, C. D. Rho, D. Rosa-Gonzalez, E. Ruiz-Velasco, H. Salazar, D. Salazar-Gallegos, A. Sandoval, M. Schneider, J. Serna-Franco, A. J. Smith, Y. Son, R. W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, E. Varela, L. Villasenor, Xiaojie Wang, I. J. Watson, E. Willox, H. Zhou

Physics Faculty Research & Creative Works

Recently, the region surrounding eHWC J1842−035 has been studied extensively by γ-ray observatories due to its extended emission reaching up to a few hundred TeV and potential as a hadronic accelerator. In this work, we use 1910 days of cumulative data from the High-Altitude Water Cherenkov (HAWC) observatory to carry out a dedicated systematic source search of the eHWC J1842−035 region. During the search, we found three sources in the region, namely, HAWC J1844−034, HAWC J1843−032, and HAWC J1846−025. We have identified HAWC J1844−034 as the extended source that emits photons with energies up to 175 TeV. We compute the …

Butte Priority Soils Operable Unit (Bpsou) Final Unreclaimed Sites – Field Sampling Plan (Fsp) Ur 42 – Area Near Walkerville Playground, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Observation Of Same-Sign Ww Production From Double Parton Scattering In Proton-Proton Collisions At √S=13 Tev, A. Tumasyan

Department of Physics and Astronomy: Faculty Publications

The first observation of the production of W^±W^± bosons from double parton scattering processes using same-sign electron-muon and dimuon events in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of 138 fb⁻¹ recorded at a center-of-mass energy of 13 TeV using the CMS detector at the CERN LHC. Multivariate discriminants are used to distinguish the signal process from the main backgrounds. A binned maximum likelihood fit is performed to extract the signal cross section. The measured cross section for production of same-sign W bosons decaying leptonically is 80.7 ± 11.2(stat)^+9.5_{-8.6 …}

Observation Of The Rare Decay Of The Η Meson To Four Muons, A. Hayrapetyan

Department of Physics and Astronomy: Faculty Publications

A search for the rare η → μ⁺μ⁻μ⁺μ⁻ double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers during 2017 and 2018 and corresponding to an integrated luminosity of 101 fb⁻¹. A signal having a statistical significance well in excess of 5 standard deviations is observed. Using the η → μ⁺μ⁻ decay as normalization, the branching fraction β(η → μ⁺μ⁻μ⁺μ⁻) = [5.0 ± 0.8(stat) ± 0.7(syst) ± …

Shallow-Water Hydrothermal Venting Linked To The Palaeocene–Eocene Thermal Maximum, Christian Berndt, Sverre Planke, Carlos A. Alvarez Zarikian, Joost Frieling, Morgan T. Jones, John M. Millett, Henk Brinkhuis, Stefan Bünz, Henrik H. Svensen, Jack Longman, Reed P. Scherer, Jens Karstens, Ben Manton, Mei Nelissen, Brandon Reed, Jan Inge Faleide, Ritske S. Huismans, Amar Agarwal, Graham D.M. Andrews, Peter Betlem, Joyeeta Bhattacharya, Sayantani Chatterjee, Marialena Christopoulou, Vincent J. Clementi, Eric C. Ferré, Irina Filina, Pengyuan Guo, Dustin T. Harper, Sarah Lambart, Geoffroy Mohn, Reina Nakaoka, Christian Tegner, Natalia Varela, Mengyuan Wang

Department of Earth and Atmospheric Sciences: Faculty Publications

The Palaeocene–Eocene Thermal Maximum (PETM) was a global warming event of 5–6 °C around 56 million years ago caused by input of carbon into the ocean and atmosphere. Hydrothermal venting of greenhouse gases produced in contact aureoles surrounding magmatic intrusions in the North Atlantic Igneous Province have been proposed to play a key role in the PETM carbon-cycle perturbation, but the precise timing, magnitude and climatic impact of such venting remains uncertain. Here we present seismic data and the results of a five-borehole transect sampling the crater of a hydrothermal vent complex in the Northeast Atlantic. Stable carbon isotope stratigraphy …

A Roadmap For The Human Gut Cell Atlas, Matthias Zilbauer, Kylie R. James, Mandeep Kaur, Sebastian Pott, Zhixin Li, Albert Burger, Jay R. Thiagarajah, Joseph Burclaff, Frode L. Jahnsen, Francesca Perrone, Alexander D. Ross, Gianluca Matteoli, Nathalie Stakenborg, Tomohisa Sujino, Andreas Moor, Raquel Bartolome-Casado, Espen S. Bækkevold, Ran Zhou, Bingqing Xie, Ken S. Lau, Shahida Din, Scott T. Magness, Qiuming Yao, Semir Beyaz, Mark Arends, Alexandre Denadai-Souza, Lori A. Coburn, Jellert T. Gaublomme, Richard Baldock, Irene Papatheodorou, Jose Ordovas-Montanes, Guy Boeckxstaens, Anna Hupalowska, Sarah A. Teichmann

School of Computing: Faculty Publications

The number of studies investigating the human gastrointestinal tract using various single-cell profiling methods has increased substantially in the past few years. Although this increase provides a unique opportunity for the generation of the first comprehensive Human Gut Cell Atlas (HGCA), there remains a range of major challenges ahead. Above all, the ultimate success will largely depend on a structured and coordinated approach that aligns global efforts undertaken by a large number of research groups. In this Roadmap, we discuss a comprehensive forward-thinking direction for the generation of the HGCA on behalf of the Gut Biological Network of the Human …

Optimizing Mn-Al Permanent Magnet Performance Through Control Of The Phase Transformation, Ternary Element Addition, And Advanced Processing, Thomas R. Keller

Dartmouth College Ph.D Dissertations

The growing need for electrical power in machines and vehicles brings with it a growing need for critical materials. The current high-performance permanent magnets (PMs) based on rare-earth (RE) elements Nd and Sm cannot escape the problem of raw material cost, geographic scarcity in the earth’s crust, and lack of circular global supply chains. This poses a problem of industrial ecology: can PMs be made from inexpensive, more abundant materials while still meeting sufficient performance criteria? PMs based on the magnetic τ phase of Mn-Al offer a possible alternative to REPMs. However, years of innovation have not yet achieved real-world …

Qc-Sane: Robust Control In Drl Using Quantile Critic With Spiking Actor And Normalized Ensemble, Surbhi Gupta, Gaurav Singal, Deepak Garg, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Recently Introduced Deep Reinforcement Learning (DRL) Techniques in Discrete-Time Have Resulted in Significant Advances in Online Games, Robotics, and So On. Inspired from Recent Developments, We Have Proposed an Approach Referred to as Quantile Critic with Spiking Actor and Normalized Ensemble (QC-SANE) for Continuous Control Problems, Which Uses Quantile Loss to Train Critic and a Spiking Neural Network (NN) to Train an Ensemble of Actors. the NN Does an Internal Normalization using a Scaled Exponential Linear Unit (SELU) Activation Function and Ensures Robustness. the Empirical Study on Multijoint Dynamics with Contact (MuJoCo)-Based Environments Shows Improved Training and Test Results Than …

Comparative Efficacy Of Systemic And Combination Fungicides For The Control Of Alternaria Leaf Spot Of Cabbage, Patience U. Ishieze, Chinedu F. Amuji, Kevin I. Ugwuoke, Paul K. Baiyeri, Michael O. Eze

Chemistry Faculty Research & Creative Works

Alternaria leaf spot of cabbage, caused by the Alternaria brassicicola, affects leaves of cabbages and often results in head rots causing severe decline in yield. in this work, the effects of systemic and combination fungicides on A. brassicicola mycelia growth in vitro and disease severity in field trials were investigated. the results of in vitro evaluation revealed that both fungicides significantly inhibited (p < 0.05) the growth of A. brassicicola under in vitro conditions. However, metal Axyl-M 6% was less effective with 100 μg/mL having only 30 ± 3.5% inhibition. on the other hand, 100 μg/mL of mancozeb 63% + carbendazim 12% had 94 ± 3.5% growth inhibition of A. brassicicola, respectively, under the same conditions. Dose-response analysis of the efficacy of the two fungicides showed that the LC50 of metal Axyl-M 6% and mancozeb 63% + carbendazim 12% were 125.52 ppm and 57.22 ppm, respectively, indicating the superiority of combination fungicide over systemic fungicide alone. Field studies showed that while manure type significantly impacted on biomass production (p < 0.001), it did not significantly affect disease severity. on the other hand, the frequency of fungicide application impacted on disease severity, with biweekly application leading to a significant reduction in disease severity after 10 weeks.

Fisheries Science Update - Western Australian Salmon Resource - September 2023, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Science Updates

Key points: 2023 stock assessment outcomes:

• The latest weight of evidence stock assessment for Western Australian salmon indicates the status of the stock is adequate and the risk to the stock is low. This means that there are no sustainability concerns for the stock.
• The Department of Primary Industries and Regional Development (DPIRD) tracks our aquatic resources by undertaking weight of evidence stock assessments on a regular basis.
• This science update follows on from the previous Western Australian salmon update in 2017.
• Detailed information on the latest stock assessment is available in Fisheries Research Report No. 336.

Area, Perimeter, Height, And Width Of Rectangle Visibility Graphs, John Caughman, Charles L. Dunn, Joshua Laison, Nancy Ann Neudauer, Colin L. Starr

Mathematics and Statistics Faculty Publications and Presentations

A rectangle visibility graph (RVG) is represented by assigning to each vertex a rectangle in the plane with horizontal and vertical sides in such a way that edges in the graph correspond to unobstructed horizontal and vertical lines of sight between their corresponding rectangles. To discretize, we consider only rectangles whose corners have integer coordinates. For any given RVG, we seek a representation with smallest bounding box as measured by its area, perimeter, height, or width (height is assumed not to exceed width).

Analysis Of Curvature Approximations Via Covariant Curl And Incompatibility For Regge Metrics, Jay Gopalakrishnan, Michael Neunteufel, Joachim Schöberl, Max Wardetzky

Mathematics and Statistics Faculty Publications and Presentations

The metric tensor of a Riemannian manifold can be approximated using Regge finite elements and such approximations can be used to compute approximations to the Gauss curvature and the Levi-Civita connection of the manifold. It is shown that certain Regge approximations yield curvature and connection approximations that converge at a higher rate than previously known. The analysis is based on covariant (distributional) curl and incompatibility operators which can be applied to piecewise smooth matrix fields whose tangential-tangential component is continuous across element interfaces. Using the properties of the canonical interpolant of the Regge space, we obtain superconvergence of approximations of …

Development Of Dibenzofuran Linkers And Phenazine-Based Redox-Responsive Foldamers, Ruth Son

Arts & Sciences Graduate Student Theses and Dissertations

Our group has demonstrated the feasibility of utilizing phenazine-1,6-dicarboxamides as redox-responsive molecular switches: changes in the oxidation state of the phenazine core forces the secondary amide arms to rotate between the doubly folded form when oxidized and the unfolded form when reduced to its dihydrophenazine form. To construct phenazine-based oligomers, we have developed dibenzofuran linkers that can easily be decorated with different solubilizing groups and incorporated into the foldamer backbone. In our initial attempts, we used xanthene linkers. However, problems with limited solubility and preference for cyclization prompted us to consider an alternative cisoid linker with a wider bite angle. …

Syntheses And Characterization Of Photoactive Ruthenium And Iron Polypyridyl Complexes, Rajani Thapa Magar

Chemistry and Chemical Biology ETDs

Within this dissertation, two distinct classes of metal complexes have been discussed that bear significance in the field of solar energy conversion, photo redox catalysis and memory devices. The first class of the metal complexes is a series of photochromic Ruthenium polypyridyl N-heterocyclic carbene tethered sulfoxide complexes that are reported to undergo unusually slow isomerization from S-bonded to O-bonded and unusually fast thermal reversion from O-bonded to S-bonded configuration. The role of NHC in the excited state dynamics of these complexes have been discussed in detail in Chapter 3.

For the first time in two decades, structural information of the …

An Activity System-Based Perspective Of Generative Ai: Challenges And Research Directions, Fiona Fui-Hoon Nah, Jingyuan Cai, Ruilin Zheng, Natalie Pang

Research Collection School Of Computing and Information Systems

With its remarkable ability to generate content, generative artificial intelligence (GAI) has been recognized as a milestone in the development of artificial general intelligence. To understand the challenges, potential impact, and implications associated with GAI, we adopt a socio-technical perspective to analyze them. First, we identify the key characteristics of GAI, which include content generation, generalization ability, and reinforcement learning based on human feedback. Next, we address technological, ethical, societal, economic, regulatory, and governance challenges. Finally, we deploy activity theory to explore research directions in GAI. Research questions that warrant further investigation include how GAI may impact the future of …

Literature Review In The Generative Ai Era: How To Make A Compelling Contribution, Shan L. Pan, Rohit Nishant, Tuure Tuunanen, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

As we write this editorial for this special issue, we are amidst the significant technological changes that are continuing to shape society. Since the emergence of ChatGPT in November 2022, humanity has become aware of the potential of generative AI (i.e., AI that can generate content) and large language models (LLMs) (i.e., AI models trained on a massive corpus of unstructured data). There is growing debate and discussion about the promise and perils of generative AI for the future of work, and academia is not immune. Premier journals in the IS domain, such as Information Systems Research, have published editorials …

Constrained Multiagent Reinforcement Learning For Large Agent Population, Jiajing Ling, Arambam James Singh, Duc Thien Nguyen, Akshat Kumar

Research Collection School Of Computing and Information Systems

Learning control policies for a large number of agents in a decentralized setting is challenging due to partial observability, uncertainty in the environment, and scalability challenges. While several scalable multiagent RL (MARL) methods have been proposed, relatively few approaches exist for large scale constrained MARL settings. To address this, we first formulate the constrained MARL problem in a collective multiagent setting where interactions among agents are governed by the aggregate count and types of agents, and do not depend on agents’ specific identities. Second, we show that standard Lagrangian relaxation methods, which are popular for single agent RL, do not …

Testsgd: Interpretable Testing Of Neural Networks Against Subtle Group Discrimination, Mengdi Zhang, Jun Sun, Jingyi Wang, Bing Sun

Research Collection School Of Computing and Information Systems

Discrimination has been shown in many machine learning applications, which calls for sufficient fairness testing before their deployment in ethic-relevant domains. One widely concerning type of discrimination, testing against group discrimination, mostly hidden, is much less studied, compared with identifying individual discrimination. In this work, we propose TestSGD, an interpretable testing approach which systematically identifies and measures hidden (which we call ‘subtle’) group discrimination of a neural network characterized by conditions over combinations of the sensitive attributes. Specifically, given a neural network, TestSGD first automatically generates an interpretable rule set which categorizes the input space into two groups. Alongside, TestSGD …

K-St: A Formal Executable Semantics Of The Structured Text Language For Plcs, Kun Wang, Jingyi Wang, Christopher M. Poskitt, Xiangxiang Chen, Jun Sun, Peng Cheng

Research Collection School Of Computing and Information Systems

Programmable Logic Controllers (PLCs) are responsible for automating process control in many industrial systems (e.g. in manufacturing and public infrastructure), and thus it is critical to ensure that they operate correctly and safely. The majority of PLCs are programmed in languages such as Structured Text (ST). However, a lack of formal semantics makes it difficult to ascertain the correctness of their translators and compilers, which vary from vendor-to-vendor. In this work, we develop K-ST, a formal executable semantics for ST in the K framework. Defined with respect to the IEC 61131-3 standard and PLC vendor manuals, K-ST is a high-level …

Automated Question Title Reformulation By Mining Modifcation Logs From Stack Overflow, Ke Liu, Xiang Chen, Chunyang Chen, Xiaofei Xie, Zhanqi Cui

Research Collection School Of Computing and Information Systems

In Stack Overflow, developers may not clarify and summarize the critical problems in the question titles due to a lack of domain knowledge or poor writing skills. Previous studies mainly focused on automatically generating the question titles by analyzing the posts’ problem descriptions and code snippets. In this study, we aim to improve title quality from the perspective of question title reformulation and propose a novel approach QETRA motivated by the findings of our formative study. Specifically, by mining modification logs from Stack Overflow, we first extract title reformulation pairs containing the original title and the reformulated title. Then we …

Endwatch: A Practical Method For Detecting Non-Termination In Real-World Software, Yao Zhang, Xiaofei Xie, Yi Li, Sen Chen, Cen Zhang, Xiaohong Li

Research Collection School Of Computing and Information Systems

Detecting non-termination is crucial for ensuring program correctness and security, such as preventing denial-of-service attacks. While termination analysis has been studied for many years, existing methods have limited scalability and are only effective on small programs. To address this issue, we propose a practical termination checking technique, called EndWatch, for detecting non-termination through testing. Specifically, we introduce two methods to generate non-termination oracles based on checking state revisits, i.e., if the program returns to a previously visited state at the same program location, it does not terminate. The non-termination oracles can be incorporated into testing tools (e.g., AFL used in …

Uncertainty-Adjusted Inductive Matrix Completion With Graph Neural Networks, Petr Kasalicky, Antoine Ledent, Rodrigo Alves

Research Collection School Of Computing and Information Systems

We propose a robust recommender systems model which performs matrix completion and a ratings-wise uncertainty estimation jointly. Whilst the prediction module is purely based on an implicit low-rank assumption imposed via nuclear norm regularization, our loss function is augmented by an uncertainty estimation module which learns an anomaly score for each individual rating via a Graph Neural Network: data points deemed more anomalous by the GNN are downregulated in the loss function used to train the low-rank module. The whole model is trained in an end-to-end fashion, allowing the anomaly detection module to tap on the supervised information available in …

Continual Collaborative Filtering Through Gradient Alignment, Dinh Hieu Do, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

A recommender system operates in a dynamic environment where new items emerge and new users join the system, resulting in ever-growing user-item interactions over time. Existing works either assume a model trained offline on a static dataset (requiring periodic re-training with ever larger datasets); or an online learning setup that favors recency over history. As privacy-aware users could hide their histories, the loss of older information means that periodic retraining may not always be feasible, while online learning may lose sight of users' long-term preferences. In this work, we adopt a continual learning perspective to collaborative filtering, by compartmentalizing users …

Revisiting The Identification Of The Co-Evolution Of Production And Test Code, Weifeng Sun, Meng Yan, Zhongxin Liu, Xin Xia, Yan Lei, David Lo

Research Collection School Of Computing and Information Systems

Many software processes advocate that the test code should co-evolve with the production code. Prior work usually studies such co-evolution based on production-test co-evolution samples mined from software repositories. A production-test co-evolution sample refers to a pair of a test code change and a production code change where the test code change triggers or is triggered by the production code change. The quality of the mined samples is critical to the reliability of research conclusions. Existing studies mined production-test co-evolution samples based on the following assumption: if a test class and its associated production class change together in one commit, …

Fair Cloud Auditing Based On Blockchain For Resource-Constrained Iot Devices, Lei Zhou, Anmin Fu, Guomin Yang, Yansong Gao, Shui Yu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Internet of Things (IoT) devices upload their data into the cloud for storage because of their limited resources. However, cloud storage data has been subject to potential integrity threats, and consequently auditing techniques are demanded to ensure the integrity of stored data. Unfortunately, existing auditing approaches require owners to undertake expensive tag calculations, which is unsuitable for resource-constrained IoT devices. To resolve the issue, we present a Fair Cloud Auditing proposal by employing the Blockchain (FCAB). We combine certificateless signatures with the designed dynamic structure to constructively offload the cost of tag computation from the IoT device to the introduced …

Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The digital economy has brought significant advancements in electronic devices, increasing convenience and comfort in people’s lives. However, this progress has also led to a shorter life cycle for these devices due to rapid advancements in hardware and software technology. As a result, e-waste collection and recycling have become vital for protecting the environment and people’s health. From the operations research perspective, the e-waste collection problem can be modeled as the Heterogeneous Vehicle Routing Problem with Multiple Time Windows (HVRP-MTW). This study proposes a metaheuristic based on the Greedy Randomized Adaptive Search Procedure complemented by Path Relinking (GRASP-PR) to solve …

When Routing Meets Recommendation: Solving Dynamic Order Recommendations Problem In Peer-To-Peer Logistics Platforms, Zhiqin Zhang, Waldy Joe, Yuyang Er, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Peer-to-Peer (P2P) logistics platforms, unlike traditional last-mile logistics providers, do not have dedicated delivery resources (both vehicles and drivers). Thus, the efficiency of such operating model lies in the successful matching of demand and supply, i.e., how to match the delivery tasks with suitable drivers that will result in successful assignment and completion of the tasks. We consider a Same-Day Delivery Problem (SDDP) involving a P2P logistics platform where new orders arrive dynamically and the platform operator needs to generate a list of recommended orders to the crowdsourced drivers. We formulate this problem as a Dynamic Order Recommendations Problem (DORP). …

Autoconf: Automated Configuration Of Unsupervised Learning Systems Using Metamorphic Testing And Bayesian Optimization, Lwin Khin Shar, Goknil Arda, Erik Johannes Husom, Sagar Sen Sen, Naing Tun Yan, Kisub Kim

Research Collection School Of Computing and Information Systems

Unsupervised learning systems using clustering have gained significant attention for numerous applications due to their unique ability to discover patterns and structures in large unlabeled datasets. However, their effectiveness highly depends on their configuration, which requires domain-specific expertise and often involves numerous manual trials. Specifically, selecting appropriate algorithms and hyperparameters adds to the com- plexity of the configuration process. In this paper, we propose, apply, and assess an automated approach (AutoConf) for config- uring unsupervised learning systems using clustering, leveraging metamorphic testing and Bayesian optimization. Metamorphic testing is utilized to verify the configurations of unsupervised learning systems by applying a …

Understanding Multi-Homing And Switching By Platform Drivers, Xiaotong Guo, Andreas Haupt, Hai Wang, Rida Qadri, Jinhua Zhao

Research Collection School Of Computing and Information Systems

Freelance drivers in the shared mobility market frequently switch or work for multiple platforms, affecting driver labor supply. Due to the importance of driver labor supply for the shared mobility market, understanding drivers’ switching and multi-homing behavior is vital to managing service quality on – and effective regulation of – mobility platforms. However, a lack of individual-level data on driver behavior has thus far impeded a deeper understanding. This paper taxonomizes and estimates perceived switching and multi-homing frictions on mobility platforms. Based on a structural model of driver labor supply, we estimate switching and multi-homing costs in a platform duopoly …