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Articles 334141 - 334170 of 5169189
Full-Text Articles in Entire DC Network
Imbalanced Graph Classification With Multi-Scale Oversampling Graph Neural Networks, Rongrong Ma, Guansong Pang, Ling Chen
Imbalanced Graph Classification With Multi-Scale Oversampling Graph Neural Networks, Rongrong Ma, Guansong Pang, Ling Chen
Research Collection School Of Computing and Information Systems
One main challenge in imbalanced graph classification is to learn expressive representations of the graphs in under-represented (minority) classes. Existing generic imbalanced learning methods, such as oversampling and imbalanced learning loss functions, can be adopted for enabling graph representation learning models to cope with this challenge. However, these methods often directly operate on the graph representations, ignoring rich discriminative information within the graphs and their interactions. To tackle this issue, we introduce a novel multi-scale oversampling graph neural network (MOSGNN) that learns expressive minority graph representations based on intra- and inter-graph semantics resulting from oversampled graphs at multiple scales - …
Cluster-Wide Task Slowdown Detection In Cloud System, Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng
Cluster-Wide Task Slowdown Detection In Cloud System, Feiyi Chen, Yingying Zhang, Lunting Fan, Yuxuan Liang, Guansong Pang, Qingsong Wen, Shuiguang Deng
Research Collection School Of Computing and Information Systems
Slow task detection is a critical problem in cloud operation and maintenance since it is highly related to user experience and can bring substantial liquidated damages. Most anomaly detection methods detect it from a single-task aspect. However, considering millions of concurrent tasks in large-scale cloud computing clusters, it becomes impractical and inefficient. Moreover, single-task slowdowns are very common and do not necessarily indicate a malfunction of a cluster due to its violent fluctuation nature in a virtual environment. Thus, we shift our attention to cluster-wide task slowdowns by utilizing the duration time distribution of tasks across a cluster, so that …
Editorial: Dsaa 2023 Journal Track On Theoretical And Practical Data Science And Analytics., Bin Yang, Feida Zhu, Wei Wei
Editorial: Dsaa 2023 Journal Track On Theoretical And Practical Data Science And Analytics., Bin Yang, Feida Zhu, Wei Wei
Research Collection School Of Computing and Information Systems
This special issue of the International Journal of Data Science and Analytics includes the DSAA 2023 Journal Track papers, which cover advances in both theoretical and practical aspects of data science and analytics, with a particular focus on trustworthy data science and analytics. The track contains nine papers, all of which underwent rigorous review by the guest editors and invited reviewers.
Quantum Relaxation For Solving Multiple Knapsack Problems, Monit Sharma, Jin Yan, Hoong Chuin Lau, Rudy Raymond
Quantum Relaxation For Solving Multiple Knapsack Problems, Monit Sharma, Jin Yan, Hoong Chuin Lau, Rudy Raymond
Research Collection School Of Computing and Information Systems
Combinatorial problems are a common challenge in business, requiring finding optimal solutions under specified constraints. While significant progress has been made with variational approaches such as QAOA, most problems addressed are unconstrained (such as Max-Cut). In this study, we investigate a hybrid quantum-classical method for constrained optimization problems, particularly those with knapsack constraints that occur frequently in financial and supply chain applications. Our proposed method relies firstly on relaxations to local quantum Hamiltonians, defined through commutative maps. Drawing inspiration from quantum random access code (QRAC) concepts, particularly Quantum Random Access Optimizer (QRAO), we explore QRAO's potential in solving large constrained …
Developer Reactions To Protestware In Open Source Software: The Cases Of Color.Js And Es5.Ext, Youmei Fan, Dong Wang, Supatsara Wattanakriengkrai, Hathaichanok Damrongsiri, Christoph Treude, Hideaki Hata, Raula Gaikovina Kula
Developer Reactions To Protestware In Open Source Software: The Cases Of Color.Js And Es5.Ext, Youmei Fan, Dong Wang, Supatsara Wattanakriengkrai, Hathaichanok Damrongsiri, Christoph Treude, Hideaki Hata, Raula Gaikovina Kula
Research Collection School Of Computing and Information Systems
There is growing concern about maintainers self-sabotaging their work in order to take political or economic stances, a practice referred to as “protestware”. Our objective is to understand the discourse around discussions on such an attack, how it is received by the community, and whether developers respond to the attack in a timely manner. We study two notable protestware cases i.e., colors.js and es5-ext. Results indicate that protestware discussions are spread more quickly on the GitHub platform, while security vulnerabilities are faster on social media. By establishing a taxonomy of protestware discussions, we identify posts that express stances and provide …
Sound And Complete Witnesses For Template-Based Verification Of Ltl Properties On Polynomial Programs, Krishnendu Chatterjee, Amir Goharshady, Ehsan Goharshady, Mehrdad Karrabi, Dorde Zikelic
Sound And Complete Witnesses For Template-Based Verification Of Ltl Properties On Polynomial Programs, Krishnendu Chatterjee, Amir Goharshady, Ehsan Goharshady, Mehrdad Karrabi, Dorde Zikelic
Research Collection School Of Computing and Information Systems
We study the classical problem of verifying programs with respect to formal specifications given in the linear temporal logic (LTL). We first present novel sound and complete witnesses for LTL verification over imperative programs. Our witnesses are applicable to both verification (proving) and refutation (finding bugs) settings. We then consider LTL formulas in which atomic propositions can be polynomial constraints and turn our focus to polynomial arithmetic programs, i.e. programs in which every assignment and guard consists only of polynomial expressions. For this setting, we provide an efficient algorithm to automatically synthesize such LTL witnesses. Our synthesis procedure is both …
Text-Driven Video Prediction, Xue Song, Jingjing Chen, Bin Zhu, Yu-Gang Jiang
Text-Driven Video Prediction, Xue Song, Jingjing Chen, Bin Zhu, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
Current video generation models usually convert signals indicating appearance and motion received from inputs (e.g., image and text) or latent spaces (e.g., noise vectors) into consecutive frames, fulfilling a stochastic generation process for the uncertainty introduced by latent code sampling. However, this generation pattern lacks deterministic constraints for both appearance and motion, leading to uncontrollable and undesirable outcomes. To this end, we propose a new task called Text-driven Video Prediction (TVP). Taking the first frame and text caption as inputs, this task aims to synthesize the following frames. Specifically, appearance and motion components are provided by the image and caption …
Aligning Human And Computational Coherence Evaluations, Jia Peng Lim, Hady Wirawan Lauw
Aligning Human And Computational Coherence Evaluations, Jia Peng Lim, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Automated coherence metrics constitute an efficient and popular way to evaluate topic models. Previous work presents a mixed picture of their presumed correlation with human judgment. This work proposes a novel sampling approach to mining topic representations at a large scale while seeking to mitigate bias from sampling, enabling the investigation of widely used automated coherence metrics via large corpora. Additionally, this article proposes a novel user study design, an amalgamation of different proxy tasks, to derive a finer insight into the human decision-making processes. This design subsumes the purpose of simple rating and outlier-detection user studies. Similar to the …
Probing Effects Of Contextual Bias On Number Magnitude Estimation, Xuehao Du, Ping Ji, Wei Qin, Lei Wang, Yunshi Lan
Probing Effects Of Contextual Bias On Number Magnitude Estimation, Xuehao Du, Ping Ji, Wei Qin, Lei Wang, Yunshi Lan
Research Collection School Of Computing and Information Systems
The semantic understanding of numbers requires association with context. However, powerful neural networks overfit spurious correlations between context and numbers in training corpus can lead to the occurrence of contextual bias, which may affect the network's accurate estimation of number magnitude when making inferences in real-world data. To investigate the resilience of current methodologies against contextual bias, we introduce a novel out-of- distribution (OOD) numerical question-answering (QA) dataset that features specific correlations between context and numbers in the training data, which are not present in the OOD test data. We evaluate the robustness of different numerical encoding and decoding methods …
Enhancing Multi-Agent System Testing With Diversity-Guided Exploration And Adaptive Critical State Exploitation, Xuyan Ma, Yawen Wang, Junjie Wang, Xiaofei Xie
Enhancing Multi-Agent System Testing With Diversity-Guided Exploration And Adaptive Critical State Exploitation, Xuyan Ma, Yawen Wang, Junjie Wang, Xiaofei Xie
Research Collection School Of Computing and Information Systems
Multi-agent systems (MASs) have achieved remarkable success in multi-robot control, intelligent transportation, and multiplayer games, etc. Thorough testing for MAS is urgently needed to ensure its robustness in the face of constantly changing and unexpected scenarios. Existing methods mainly focus on single-agent system testing and cannot be directly applied to MAS testing due to the complexity of MAS. To our best knowledge, there are fewer studies on MAS testing. While several studies have focused on adversarial attacks on MASs, they primarily target failure detection from an attack perspective, i.e., discovering failure scenarios, while ignoring the diversity of scenarios. In this …
Ft2ra: A Fine-Tuning-Inspired Approach To Retrieval-Augmented Code Completion, Qi Guo, Shangqing Liu, Xiaofei Xie, Ze Tang Tang
Ft2ra: A Fine-Tuning-Inspired Approach To Retrieval-Augmented Code Completion, Qi Guo, Shangqing Liu, Xiaofei Xie, Ze Tang Tang
Research Collection School Of Computing and Information Systems
The rise of code pre-trained models has significantly enhanced various coding tasks, such as code completion, and tools like GitHub Copilot. However, the substantial size of these models, especially large models, poses a significant challenge when it comes to fine-tuning them for specific downstream tasks. As an alternative approach, retrieval-based methods have emerged as a promising solution, augmenting model predictions without the need for fine-tuning. Despite their potential, a significant challenge is that the designs of these methods often rely on heuristics, leaving critical questions about what information should be stored or retrieved and how to interpolate such information for …
Bugs In Pods: Understanding Bugs In Container Runtime Systems, Jiongchi Yu, Xiaofei Xie, Ceng Zhang, Sen Chen
Bugs In Pods: Understanding Bugs In Container Runtime Systems, Jiongchi Yu, Xiaofei Xie, Ceng Zhang, Sen Chen
Research Collection School Of Computing and Information Systems
Container Runtime Systems (CRSs), which form the foundational infrastructure of container clouds, are critically important due to their impact on the quality of container cloud implementations. However, a comprehensive understanding of the quality issues present in CRS implementations remains lacking. To bridge this gap, we conduct the first comprehensive empirical study of CRS bugs. Specifically, we gather 429 bugs from 8,271 commits across dominant CRS projects, including runc, gvisor, containerd, and cri-o. Through manual analysis, we develop taxonomies of CRS bug symptoms and root causes, comprising 16 and 13 categories, respectively. Furthermore, we evaluate the capability of popular testing approaches, …
How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation, Cen Zhang, Yaowen Zheng, Mingqiang Bai, Yeting Li, Wei Ma, Xiaofei Xie
How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation, Cen Zhang, Yaowen Zheng, Mingqiang Bai, Yeting Li, Wei Ma, Xiaofei Xie
Research Collection School Of Computing and Information Systems
Fuzz drivers are essential for library API fuzzing. However, automatically generating fuzz drivers is a complex task, as it demands the creation of high-quality, correct, and robust API usage code. An LLM-based (Large Language Model) approach for generating fuzz drivers is a promising area of research. Unlike traditional program analysis-based generators, this text-based approach is more generalized and capable of harnessing a variety of API usage information, resulting in code that is friendly for human readers. However, there is still a lack of understanding regarding the fundamental issues on this direction, such as its e ectiveness and potential challenges. To …
A Two-Stage Matheuristic For The Home Healthcare Routing And Scheduling Problem With Perishable Products, Aldy Gunawan, Nabila Yuraisyah Salsabila, Vincent F. Yu, Pham Kien Minh Nguyen
A Two-Stage Matheuristic For The Home Healthcare Routing And Scheduling Problem With Perishable Products, Aldy Gunawan, Nabila Yuraisyah Salsabila, Vincent F. Yu, Pham Kien Minh Nguyen
Research Collection School Of Computing and Information Systems
This study proposes a home healthcare routing and scheduling problem, where perishable products such as medicines, vaccines, or meals must be provided for some patients’ treatments. This problem is formulated as a mixed integer linear programming (MILP). A two-stage matheuristic is then developed as the solution approach. The first stage is a local search to solve the nurse routing problem, and the second stage is run as the relaxed MILP to solve the scheduling problem. The matheuristic is tested on newly generated instances and compared with the results of CPLEX. The proposed matheuristic is able to obtain CPLEX solutions within …
September 2024 News Releases, University Of Montana--Missoula. Office Of University Relations
September 2024 News Releases, University Of Montana--Missoula. Office Of University Relations
University of Montana News Releases, 1928, 1956-present
No abstract provided.
Isokinetic Strength And Jumping Abilities Of Teenage Soccer Players Playing In Different Field Positions, Michal Gorski, Adrian Wilk, Anna Pastuszak, Michal Starczewski, Bartlomiej Michalak, Michael Lane, Krzysztof Busko
Isokinetic Strength And Jumping Abilities Of Teenage Soccer Players Playing In Different Field Positions, Michal Gorski, Adrian Wilk, Anna Pastuszak, Michal Starczewski, Bartlomiej Michalak, Michael Lane, Krzysztof Busko
EKU Faculty and Staff Scholarship
Soccer is a sport being performed in a very dynamic manner. It requires soccer players to be able to develop high muscle force in a very short period of time. The aim of the study was to evaluate the strength and jumping abilities of young soccer players playing in different positions on the field. The study included 49 adolescent soccer players: 6 goalkeepers, 15 defenders, 17 midfielders and 11 strikers. We measured peak torques (PT), total work (TW), and average power (AP) developed by the knee flexors and extensors under isokinetic conditions at angular velocities of 60°⋅s-1, 180°⋅s-1 and 300°⋅s-1 …
Simple And Epididymal-Sparing Orchiectomy For Surgical Castration In Stage Iv Prostate Cancer, Harrison Travis, Michael Dubic, Joseph Bardot, Blane Edwards, Jessie R. Gills, Scott E. Delacroix, Stephen Lacour, Matthew Mutter, Donald Bell, Mary E. Westerman
Simple And Epididymal-Sparing Orchiectomy For Surgical Castration In Stage Iv Prostate Cancer, Harrison Travis, Michael Dubic, Joseph Bardot, Blane Edwards, Jessie R. Gills, Scott E. Delacroix, Stephen Lacour, Matthew Mutter, Donald Bell, Mary E. Westerman
School of Medicine Faculty Publications
Background: Androgen deprivation therapy, the mainstay of treatment for patients with advanced prostate cancer, can be either medical or surgical. Surgery has cost benefits compared to medical treatment. In this study, we evaluated the use of simple and epididymal-sparing orchiectomy in 2 different practice settings for the treatment of metastatic prostate cancer. Methods: We reviewed patients who underwent surgical castration for metastatic prostate cancer between 2011 and 2022. The primary outcome was achieving castration-level total testosterone of /dL. We also compared the characteristics of patients who were seen at a public academic teaching hospital vs those who were seen at …
A Pilot Program To Improve Tb Care With Primary And Specialty Care Coordination In Tb Public Health Clinic, Priyanka Jadhav, Gabrielle Boudoin, R Miles, Shandrica Seymour, J Parham, Amy Wolfe, Juzar Ali
A Pilot Program To Improve Tb Care With Primary And Specialty Care Coordination In Tb Public Health Clinic, Priyanka Jadhav, Gabrielle Boudoin, R Miles, Shandrica Seymour, J Parham, Amy Wolfe, Juzar Ali
School of Medicine Faculty Publications
BACKGROUND: The Wetmore Tuberculosis (TB) Clinic in New Orleans serves patients who often lack primary care (PC) or specialty care (SC), which is complicated by comorbidities. An initiative to provide on-site PC and coordinate care aims to enhance TB patient management. METHODS: Data collection involved categorizing patients based on their PC status: Group I (regular PC), Group II (intermittent PC), and Group III (no PC), with on-site Nurse Practitioner-based Bridge Care (NPBC) provided as needed. RESULTS: Over 12 months, 209 out of 354 patients required NPBC and PC/SC coordination, with a 20% shift from Group III to Group I, reducing …
Biom 594.01: Molecular And Biomedical Sciences Professional Seminar, Brent J. Ryckman
Biom 594.01: Molecular And Biomedical Sciences Professional Seminar, Brent J. Ryckman
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Chmy 401.01: Advanced Inorganic Chemistry, Dong Wang
Chmy 401.01: Advanced Inorganic Chemistry, Dong Wang
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Crwr 515.01: Traditional Prosody, Donald L. Hill
Crwr 515.01: Traditional Prosody, Donald L. Hill
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Phsx 311.01: Oscillations And Waves, Chantenelle M. Nava
Phsx 311.01: Oscillations And Waves, Chantenelle M. Nava
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Psyx 280.01: Fundamentals Of Memory And Cognition, Yoonhee Jang
Psyx 280.01: Fundamentals Of Memory And Cognition, Yoonhee Jang
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Grmn 101.03: Elementary German I, Marton M. Marko
Grmn 101.03: Elementary German I, Marton M. Marko
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Spns 201.80: Intermediate Spanish I - Homors, Micaela O. Downey
Spns 201.80: Intermediate Spanish I - Homors, Micaela O. Downey
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Edu 497.02: Methods: K-8 Social Studies, Matthew V. Schertz
Edu 497.02: Methods: K-8 Social Studies, Matthew V. Schertz
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Arth 334h.01: Architectural History Ii, Michael T. Monsos
Arth 334h.01: Architectural History Ii, Michael T. Monsos
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Hee 302.01: Methods Of Instructional Strategies In Elementary Physical Education, Thomas S. Hersee
Hee 302.01: Methods Of Instructional Strategies In Elementary Physical Education, Thomas S. Hersee
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Jrnl 350.01: Intermediate Video Photography, Jeremy J. Lurgio
Jrnl 350.01: Intermediate Video Photography, Jeremy J. Lurgio
University of Montana Course Syllabi, 2021-2025
No abstract provided.
Psyx 430.01: Counseling Theories In Context, Daniel J. Salois
Psyx 430.01: Counseling Theories In Context, Daniel J. Salois
University of Montana Course Syllabi, 2021-2025
No abstract provided.