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Articles 5251 - 5280 of 302428

Full-Text Articles in Physical Sciences and Mathematics

Universality Class Of A Spinor Bose–Einstein Condensate Far From Equilibrium, Seung Jung Huh, Koushik Mukherjee, Kiryang Kwon, Jihoon Seo, Junhyeok Hur, Simeon I. Mistakidis, H. R. Sadeghpour, Jae Yoon Choi Mar 2024

Universality Class Of A Spinor Bose–Einstein Condensate Far From Equilibrium, Seung Jung Huh, Koushik Mukherjee, Kiryang Kwon, Jihoon Seo, Junhyeok Hur, Simeon I. Mistakidis, H. R. Sadeghpour, Jae Yoon Choi

Physics Faculty Research & Creative Works

Scale Invariance And Self-Similarity In Physics Provide A Unified Framework For Classifying Phases Of Matter And Dynamical Properties Near Equilibrium In Both Classical And Quantum Systems. This Paradigm Has Been Further Extended To Isolated Many-Body Quantum Systems Driven Far From Equilibrium, For Which The Physical Observables Exhibit Dynamical Scaling With Universal Scaling Exponents. Universal Dynamics Appear In A Wide Range Of Scenarios, Including Cosmology, Quark–gluon Matter, Ultracold Atoms And Quantum Spin Magnets. However, How The Universal Dynamics Depend On The Symmetry Of The Underlying Hamiltonian In Non-Equilibrium Systems Remains An Outstanding Challenge. Here We Report On The Classification Of Universal …

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Considering The Impact Framework To Understand The Ai-Well-Being-Complex From An Interdisciplinary Perspective, Christian Montag, Preslav Nakov, Raian Ali Mar 2024

Considering The Impact Framework To Understand The Ai-Well-Being-Complex From An Interdisciplinary Perspective, Christian Montag, Preslav Nakov, Raian Ali

Natural Language Processing Faculty Publications

Artificial intelligence (AI) is built into many products and has the potential to dramatically impact societies around the world. This short theoretical paper aims to provide a simple framework that might help us understand how the introduction and/or use of products with AI might influence the well-being of humans. It is proposed that considering the dynamic Interplay between variables stemming from Modality, Person, Area, Culture and Transparency categories will help to understand the influence of AI on well-being. The Modality category encompasses areas such as the degree of AI being interactive, informational versus actualizing, or autonomous. The Person variable contains …

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Pollinator Communities And Their Ecosystem Services At Conservation Grasslands And Adjacent Croplands, Araceli Gomez Villegas Mar 2024

Pollinator Communities And Their Ecosystem Services At Conservation Grasslands And Adjacent Croplands, Araceli Gomez Villegas

Department of Entomology: Dissertations, Theses, and Student Research

Pollinators are intrinsically linked to the success of unmanaged and managed ecosystems by providing pollination services that aid in the reproduction of wildflowers and many crops. Land use change, habitat loss, fragmentation, and related landscape-level phenomena (for example, increased pesticide exposure) threaten pollinators and have been associated with population declines. In the Midwestern region of the United States, land conversion of native prairies and grasslands to row-crop agriculture has been one of the largest contributors to pollinator habitat loss. Conservation programs, such as the Conservation Reserve Program, have worked towards removing environmentally sensitive lands from agriculture production and enrolling them …

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2024 March - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University Mar 2024

2024 March - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

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Using Flipped Classroom Modules To Facilitate Higher Order Learning In Undergraduate Organic Chemistry, Lauren R. Holloway, Tabitha Miller, Bryce Da Camara, Paul M. Bogie, Briana L. Hickey, Jack Barbera, Angie L. Lopez, Multiple Additional Authors Mar 2024

Using Flipped Classroom Modules To Facilitate Higher Order Learning In Undergraduate Organic Chemistry, Lauren R. Holloway, Tabitha Miller, Bryce Da Camara, Paul M. Bogie, Briana L. Hickey, Jack Barbera, Angie L. Lopez, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

In an ongoing effort to incorporate active learning and promote higher order learning outcomes in undergraduate organic chemistry, a hybrid (“flipped”) classroom structure has been used to facilitate a series of collaborative activities in the first two courses of the lower division organic chemistry sequence. An observational study of seven classes over a five-year period reveals there is a strong correlation between performance on the in-class activities and performance on the final exam across all classes; however, a significant number of students in these courses continue to struggle on both the in-class activities and final exam. The Activity Engagement Survey …

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The Α-Crystallin Chaperones Undergo A Quasi-Ordered Co-Aggregation Process In Response To Saturating Client Interaction, Kirsten Lampi, Adam P. Miller, Susan E. O'Neill, Steve L. Reichow Mar 2024

The Α-Crystallin Chaperones Undergo A Quasi-Ordered Co-Aggregation Process In Response To Saturating Client Interaction, Kirsten Lampi, Adam P. Miller, Susan E. O'Neill, Steve L. Reichow

Chemistry Faculty Publications and Presentations

Small heat shock proteins (sHSPs) are ATP-independent chaperones vital to cellular proteostasis, preventing protein aggregation events linked to various human diseases including cataract. The α-crystallins, αA-crystallin (αAc) and αB-crystallin (αBc), represent archetypal sHSPs that exhibit complex polydispersed oligomeric assemblies and rapid subunit exchange dynamics. Yet, our understanding of how this plasticity contributes to chaperone function remains poorly understood. This study investigates structural changes in αAc and αBc during client sequestration under varying degree of chaperone saturation. Using biochemical and biophysical analyses combined with single-particle electron microscopy (EM), we examined αAc and αBc in their apo-states and at various stages of …

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Dna-Based Assay For Calorimetric Determination Of Protein Concentrations In Pure Or Mixed Solutions, Matthew W. Eskew, Patrick Reardon, Albert S. Benight Mar 2024

Dna-Based Assay For Calorimetric Determination Of Protein Concentrations In Pure Or Mixed Solutions, Matthew W. Eskew, Patrick Reardon, Albert S. Benight

Chemistry Faculty Publications and Presentations

It was recently reported that values of the transition heat capacities, as measured by differential scanning calorimetry, for two globular proteins and a short DNA hairpin in NaCl buffer are essentially equivalent, at equal concentrations (mg/mL). To validate the broad applicability of this phenomenon, additional evidence for this equivalence is presented that reveals it does not depend on DNA sequence, buffer salt, or transition temperature (Tm). Based on the equivalence of transition heat capacities, a calorimetric method was devised to determine protein concentrations in pure and complex solutions. The scheme uses direct comparisons between the thermodynamic stability of a short …

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Simulated Annealing With Reinforcement Learning For The Set Team Orienteering Problem With Time Windows, Vincent F. Yu, Nabila Y. Salsabila, Shih-W Lin, Aldy Gunawan Mar 2024

Simulated Annealing With Reinforcement Learning For The Set Team Orienteering Problem With Time Windows, Vincent F. Yu, Nabila Y. Salsabila, Shih-W Lin, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This research investigates the Set Team Orienteering Problem with Time Windows (STOPTW), a new variant of the well-known Team Orienteering Problem with Time Windows and Set Orienteering Problem. In the STOPTW, customers are grouped into clusters. Each cluster is associated with a profit attainable when a customer in the cluster is visited within the customer's time window. A Mixed Integer Linear Programming model is formulated for STOPTW to maximizing total profit while adhering to time window constraints. Since STOPTW is an NP-hard problem, a Simulated Annealing with Reinforcement Learning (SARL) algorithm is developed. The proposed SARL incorporates the core concepts …

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Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink Mar 2024

Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink

Research Collection School Of Computing and Information Systems

Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …

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Technical Memorandum Grove Gulch Earth Volumetric Studio Model Inputs, Josh Bryson Mar 2024

Technical Memorandum Grove Gulch Earth Volumetric Studio Model Inputs, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Non-Monotonic Generation Of Knowledge Paths For Context Understanding, Pei-Chi Lo, Ee-Peng Lim Mar 2024

Non-Monotonic Generation Of Knowledge Paths For Context Understanding, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Knowledge graphs can be used to enhance text search and access by augmenting textual content with relevant background knowledge. While many large knowledge graphs are available, using them to make semantic connections between entities mentioned in the textual content remains to be a difficult task. In this work, we therefore introduce contextual path generation (CPG) which refers to the task of generating knowledge paths, contextual path, to explain the semantic connections between entities mentioned in textual documents with given knowledge graph. To perform CPG task well, one has to address its three challenges, namely path relevance, incomplete knowledge graph, and …

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Stopguess: A Framework For Public-Key Authenticated Encryption With Keyword Search, Tao Xiang, Zhongming Wang, Biwen Chen, Xiaoguo Li, Peng Wang, Fei Chen Mar 2024

Stopguess: A Framework For Public-Key Authenticated Encryption With Keyword Search, Tao Xiang, Zhongming Wang, Biwen Chen, Xiaoguo Li, Peng Wang, Fei Chen

Research Collection School Of Computing and Information Systems

Public key encryption with keyword search (PEKS) allows users to search on encrypted data without leaking the keyword information from the ciphertexts. But it does not preserve keyword privacy within the trapdoors, because an adversary (e.g., untrusted server) might launch inside keyword-guessing attacks (IKGA) to guess keywords from the trapdoors. In recent years, public key authenticated encryption with keyword search (PAEKS) has become a promising primitive to counter the IKGA. However, existing PAEKS schemes focus on the concrete construction of PAEKS, making them unable to support modular construction, intuitive proof, or flexible extension. In this paper, our proposal called “StopGuess” …

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Screening Through A Broad Pool: Towards Better Diversity For Lexically Constrained Text Generation, Changsen Yuan, Heyan Huang, Yixin Cao, Qianwen Cao Mar 2024

Screening Through A Broad Pool: Towards Better Diversity For Lexically Constrained Text Generation, Changsen Yuan, Heyan Huang, Yixin Cao, Qianwen Cao

Research Collection School Of Computing and Information Systems

Lexically constrained text generation (CTG) is to generate text that contains given constrained keywords. However, the text diversity of existing models is still unsatisfactory. In this paper, we propose a lightweight dynamic refinement strategy that aims at increasing the randomness of inference to improve generation richness and diversity while maintaining a high level of fluidity and integrity. Our basic idea is to enlarge the number and length of candidate sentences in each iteration, and choose the best for subsequent refinement. On the one hand, different from previous works, which carefully insert one token between two words per action, we insert …

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Sigmadiff: Semantics-Aware Deep Graph Matching For Pseudocode Diffing, Lian Gao, Yu Qu, Sheng Yu, Yue Duan, Heng Yin Mar 2024

Sigmadiff: Semantics-Aware Deep Graph Matching For Pseudocode Diffing, Lian Gao, Yu Qu, Sheng Yu, Yue Duan, Heng Yin

Research Collection School Of Computing and Information Systems

Pseudocode diffing precisely locates similar parts and captures differences between the decompiled pseudocode of two given binaries. It is particularly useful in many security scenarios such as code plagiarism detection, lineage analysis, patch, vulnerability analysis, etc. However, existing pseudocode diffing and binary diffing tools suffer from low accuracy and poor scalability, since they either rely on manually-designed heuristics (e.g., Diaphora) or heavy computations like matrix factorization (e.g., DeepBinDiff). To address the limitations, in this paper, we propose a semantics-aware, deep neural network-based model called SIGMADIFF. SIGMADIFF first constructs IR (Intermediate Representation) level interprocedural program dependency graphs (IPDGs). Then it uses …

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T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng Mar 2024

T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng

Research Collection School Of Computing and Information Systems

Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory …

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Harnessing The Advances Of Meda To Optimize Multi-Puf For Enhancing Ip Security Of Biochips, Chen Dong, Xiaodong Guo, Sihuang Lian, Yinan Yao, Zhenyi Chen, Yang Yang, Zhanghui Liu Mar 2024

Harnessing The Advances Of Meda To Optimize Multi-Puf For Enhancing Ip Security Of Biochips, Chen Dong, Xiaodong Guo, Sihuang Lian, Yinan Yao, Zhenyi Chen, Yang Yang, Zhanghui Liu

Research Collection School Of Computing and Information Systems

Digital microfluidic biochips (DMFBs) have a significant stride in the applications of medicine and the biochemistry in recent years. DMFBs based on micro-electrode-dot-array (MEDA) architecture, as the next-generation DMFBs, aim to overcome drawbacks of conventional DMFBs, such as droplet size restriction, low accuracy, and poor sensing ability. Since the potential market value of MEDA biochips is vast, it is of paramount importance to explore approaches to protect the intellectual property (IP) of MEDA biochips during the development process. In this paper, an IP authentication strategy based on the multi-PUF applied to MEDA biochips is presented, called bioMPUF, consisting of Delay …

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Hypergraphs With Attention On Reviews For Explainable Recommendation, Theis E. Jendal, Trung Hoang Le, Hady Wirawan Lauw, Matteo Lissandrini, Peter Dolog, Katja Hose Mar 2024

Hypergraphs With Attention On Reviews For Explainable Recommendation, Theis E. Jendal, Trung Hoang Le, Hady Wirawan Lauw, Matteo Lissandrini, Peter Dolog, Katja Hose

Research Collection School Of Computing and Information Systems

Given a recommender system based on reviews, the challenges are how to effectively represent the review data and how to explain the produced recommendations. We propose a novel review-specific Hypergraph (HG) model, and further introduce a model-agnostic explainability module. The HG model captures high-order connections between users, items, aspects, and opinions while maintaining information about the review. The explainability module can use the HG model to explain a prediction generated by any model. We propose a path-restricted review-selection method biased by the user preference for item reviews and propose a novel explanation method based on a review graph. Experiments on …

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Meta-Interpretive Learning With Reuse, Rong Wang, Jun Sun, Cong Tian, Zhenhua Duan Mar 2024

Meta-Interpretive Learning With Reuse, Rong Wang, Jun Sun, Cong Tian, Zhenhua Duan

Research Collection School Of Computing and Information Systems

Inductive Logic Programming (ILP) is a research field at the intersection between machine learning and logic programming, focusing on developing a formal framework for inductively learning relational descriptions in the form of logic programs from examples and background knowledge. As an emerging method of ILP, Meta-Interpretive Learning (MIL) leverages the specialization of a set of higher-order metarules to learn logic programs. In MIL, the input includes a set of examples, background knowledge, and a set of metarules, while the output is a logic program. MIL executes a depth-first traversal search, where its program search space expands polynomially with the number …

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Temporal Implicit Multimodal Networks For Investment And Risk Management, Meng Kiat Gary Ang, Ee-Peng Lim Mar 2024

Temporal Implicit Multimodal Networks For Investment And Risk Management, Meng Kiat Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Many deep learning works on financial time-series forecasting focus on predicting future prices/returns of individual assets with numerical price-related information for trading, and hence propose models designed for univariate, single-task, and/or unimodal settings. Forecasting for investment and risk management involves multiple tasks in multivariate settings: forecasts of expected returns and risks of assets in portfolios, and correlations between these assets. As different sources/types of time-series influence future returns, risks, and correlations of assets in different ways, it is also important to capture time-series from different modalities. Hence, this article addresses financial time-series forecasting for investment and risk management in a …

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Application Of Collaborative Learning Paradigms Within Software Engineering Education: A Systematic Mapping Study, Rita Garcia, Christoph Treude, Andrew Valentine Mar 2024

Application Of Collaborative Learning Paradigms Within Software Engineering Education: A Systematic Mapping Study, Rita Garcia, Christoph Treude, Andrew Valentine

Research Collection School Of Computing and Information Systems

Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE educators can use Collaborative Learning (CL) to help students develop collaboration skills. This paper uses a Systematic Mapping Study (SMS) to examine the application of the CL educational theory in SE Education. The SMS identified 14 papers published between 2011 and 2022. We used qualitative analysis to classify the papers into four CL paradigms: Conditions, Effect, Interactions, and Computer-Supported Collaborative Learning (CSCL). We found a high interest in CSCL, with a shift in student interaction research …

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Win: Weight-Decay-Integrated Nesterov Acceleration For Faster Network Training, Pan Zhou, Xingyu Xie, Zhouchen Lin, Kim-Chuan Toh, Shuicheng Yan Mar 2024

Win: Weight-Decay-Integrated Nesterov Acceleration For Faster Network Training, Pan Zhou, Xingyu Xie, Zhouchen Lin, Kim-Chuan Toh, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Training deep networks on large-scale datasets is computationally challenging. This work explores the problem of “how to accelerate adaptive gradient algorithms in a general manner", and proposes an effective Weight-decay-Integrated Nesterov acceleration (Win) to accelerate adaptive algorithms. Taking AdamW and Adam as examples, per iteration, we construct a dynamical loss that combines the vanilla training loss and a dynamic regularizer inspired by proximal point method, and respectively minimize the first- and second-order Taylor approximations of dynamical loss to update variable. This yields our Win acceleration that uses a conservative step and an aggressive step to update, and linearly combines these …

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Pa2blo: Low-Power, Personalized Audio Badge, Hemanth Sabbella, Dulaj Sanjaya Weerakoon, Manoj Gulati, Archan Misra Mar 2024

Pa2blo: Low-Power, Personalized Audio Badge, Hemanth Sabbella, Dulaj Sanjaya Weerakoon, Manoj Gulati, Archan Misra

Research Collection School Of Computing and Information Systems

We present the hardware design and software pipeline for an ultra-low power device, in the form factor of a wearable badge, that supports energy efficient sensing, processing and wireless transfer of human voice commands and interactions. The proposed system, called PA2BLO, is envisioned to support both: (a) real-time, scalable, authorized voice based interaction and control of devices and appliances, and (b) longitudinal, low-power logging of natural voice interactions. PA2BLO in-troduces two key novel capabilities. First, it includes a low power, low-complexity voice authentication module that is able to reliably authenticate an authorized user only using low sampling rate (500 Hz) …

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Representation Learning For Stack Overflow Posts: How Far Are We?, Junda He, Xin Zhou, Bowen Xu, Ting Zhang, Kisub Kim, Zhou Yang, Thung Ferdian, Ivana Clairine Irsan, David Lo Mar 2024

Representation Learning For Stack Overflow Posts: How Far Are We?, Junda He, Xin Zhou, Bowen Xu, Ting Zhang, Kisub Kim, Zhou Yang, Thung Ferdian, Ivana Clairine Irsan, David Lo

Research Collection School Of Computing and Information Systems

The tremendous success of Stack Overflow has accumulated an extensive corpus of software engineering knowledge, thus motivating researchers to propose various solutions for analyzing its content. The performance of such solutions hinges significantly on the selection of representation models for Stack Overflow posts. As the volume of literature on Stack Overflow continues to burgeon, it highlights the need for a powerful Stack Overflow post representation model and drives researchers’ interest in developing specialized representation models that can adeptly capture the intricacies of Stack Overflow posts. The state-of-the-art (SOTA) Stack Overflow post representation models are Post2Vec and BERTOverflow, which are built …

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Demystifying Faulty Code: Step-By-Step Reasoning For Explainable Fault Localization, Ratnadira Widyasari, Jia Wei Ang, Truong Giang Nguyen, Neil Sharma, David Lo Mar 2024

Demystifying Faulty Code: Step-By-Step Reasoning For Explainable Fault Localization, Ratnadira Widyasari, Jia Wei Ang, Truong Giang Nguyen, Neil Sharma, David Lo

Research Collection School Of Computing and Information Systems

Fault localization is a critical process that involves identifying specific program elements responsible for program failures. Manually pinpointing these elements, such as classes, methods, or statements, which are associated with a fault is laborious and time-consuming. To overcome this challenge, various fault localization tools have been developed. These tools typically generate a ranked list of suspicious program elements. However, this information alone is insufficient. A prior study emphasized that automated fault localization should offer a rationale. In this study, we investigate the step-by-step reasoning for explainable fault localization. We explore the potential of Large Language Models (LLM) in assisting developers …

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Stability Verification In Stochastic Control Systems Via Neural Network Supermartingales, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger Mar 2024

Stability Verification In Stochastic Control Systems Via Neural Network Supermartingales, Mathias Lechner, Dorde Zikelic, Krishnendu Chatterjee, Thomas A. Henzinger

Research Collection School Of Computing and Information Systems

We consider the problem of formally verifying almost-sure (a.s.) asymptotic stability in discrete-time nonlinear stochastic control systems. While verifying stability in deterministic control systems is extensively studied in the literature, verifying stability in stochastic control systems is an open problem. The few existing works on this topic either consider only specialized forms of stochasticity or make restrictive assumptions on the system, rendering them inapplicable to learning algorithms with neural network policies. In this work, we present an approach for general nonlinear stochastic control problems with two novel aspects: (a) instead of classical stochastic extensions of Lyapunov functions, we use ranking …

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Fixing Your Own Smells: Adding A Mistake-Based Familiarization Step When Teaching Code Refactoring, Ivan Wei Han Tan, Christopher M. Poskitt Mar 2024

Fixing Your Own Smells: Adding A Mistake-Based Familiarization Step When Teaching Code Refactoring, Ivan Wei Han Tan, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Programming problems can be solved in a multitude of functionally correct ways, but the quality of these solutions (e.g. readability, maintainability) can vary immensely. When code quality is poor, symptoms emerge in the form of 'code smells', which are specific negative characteristics (e.g. duplicate code) that can be resolved by applying refactoring patterns. Many undergraduate computing curricula train students on this software engineering practice, often doing so via exercises on unfamiliar instructor-provided code. Our observation, however, is that this makes it harder for novices to internalise refactoring as part of their own development practices. In this paper, we propose a …

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2024 Draft Final Silver Bow Creek Conservation Area Repository Data Gap Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc. Mar 2024

2024 Draft Final Silver Bow Creek Conservation Area Repository Data Gap Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Grove Gulch Sedimentation Bay Final Remedial Design Report, Woodard & Curran Mar 2024

Grove Gulch Sedimentation Bay Final Remedial Design Report, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Health And Safety Plan (Hasp) Butte Priority Soils Operable Unit, Woodard & Curran Mar 2024

Health And Safety Plan (Hasp) Butte Priority Soils Operable Unit, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2022, Pioneer Technical Services, Inc. Mar 2024

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2022, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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