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37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Sun, Yifei Song, Cheng Lu, Feng Li, Wei Jin, Hai Zomaya, Albert Y. National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Centre for Distributed and High Performance Computing School of Computer Science University of Sydney Australia

ISBN: (纸本)9781577358800

Machine learning models are increasingly used in time series prediction with promising results. The model explanation of time series prediction falls behind the model development and makes less sense to users in understanding model decisions. This paper proposes ES-Mask, a post-hoc and model-agnostic evolutionary strip mask-based saliency approach for time series applications. ES-Mask designs the mask consisting of strips with the same salient value in consecutive time steps to produce binary and sustained feature importance scores over time for easy understanding and interpretation of time series. ES-Mask uses an evolutionary algorithm to search for the optimal mask by manipulating strips in rounds, thus is agnostic to models by involving no internal model states in the search. The initial experiments on MIMIC-III data set show that ES-Mask outperforms state-of-the-art methods. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Time series

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Transforming desalination brine into highly reactive magnesium oxide and life cycle analysis

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Watershed Ecology and the Environment 2025年 7卷 36-46页

作者： Senevirathna, Hasanthi L. Lee, W.P. Cathie Wu, Shunnian Bai, Kewu Wu, Ping Entropic Interface Group Engineering Product Development Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Institute of High-Performance Computing Agency for Science Technology and Research Fusionopolis Way #16-16 Connexis 138632 Singapore

The sustainable production of magnesium oxide (MgO) from reject brine at a desalination facility in Singapore presents a promising alternative to traditional building materials. This study investigates the properties and extraction methods of MgO derived from reject brine, focusing on environmental sustainability and resource efficiency. By utilizing a combination of thermodynamic modelling of concentrated salt aqueous solutions and experimental validation, we optimized the recovery process for Mg²⁺ from reject brine, achieving an impressive 99 % recovery rate to produce MgO with ∼ 98 % purity. The MgO produced, calcined at 700 °C, exhibits high reactivity and a large surface area of 58.01 m²/g, making it a highly viable option for various industrial applications. This approach addresses reject brine disposal challenges and emphasizes brine valorization, aligning with strict environmental regulations by treating both freshwater and concentrated brine as valuable products. The technology enables cost-effective reject brine treatment by recycling Mg²⁺ to produce sustainable Mg-based materials. A comprehensive Life Cycle Assessment (LCA) was conducted to evaluate the environmental impact of MgO production from reject brine. This analysis provides a thorough examination of the transformation process, assessing the sustainability of employing MgO in commercial applications. The findings of this study offer valuable insights for enhancing sustainability in various sectors, underscoring the promise of MgO as an environmentally friendly and cost-effective material. © 2025 The Authors

关键词： CO2 emission MgO Reactivity Reject brine Solution model

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PSST: A Benchmark for Evaluation-driven Text Public-Speaking Style Transfer

PSST: A Benchmark for Evaluation-driven Text Public-Speaking...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Sun, Huashan Wu, Yixiao Ye, Yuhao Yang, Yizhe Li, Yinghao Li, Jiawei Gao, Yang School of Computer Science and Technology Beijing Institute of Technology Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China

ISBN: (纸本)9798891761681

Language style is necessary for AI systems to understand and generate diverse human language ***, previous text style transfer primarily focused on sentence-level data-driven approaches, limiting exploration of potential problems in large language models (LLMs) and the ability to meet complex application *** overcome these limitations, we introduce a novel task called Public-Speaking Style Transfer (PSST), which aims to simulate humans to transform passage-level, official texts into a public-speaking *** in the analysis of real-world data from a linguistic perspective, we decompose public-speaking style into key sub-styles to pose challenges and quantify the style modeling capability of *** such intricate text style transfer, we further propose a fine-grained evaluation framework to analyze the characteristics and identify the problems of stylized *** experiments suggest that current LLMs struggle to generate public speaking texts that align with human preferences, primarily due to excessive stylization and loss of semantic information. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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ON THE DISTRIBUTION OF AERODYNAMIC LOAD AND STRESS ON WIND TURBINE BLADE 42

ON THE DISTRIBUTION OF AERODYNAMIC LOAD AND STRESS ON WIND T...

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ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2023

作者： Dao, My Ha Le, Quang Tuyen Zhao, Xiang Institute of High Performance Computing Agency for Science Technology and Research Singapore 1 Fusionopolis Way #16-16 Connexis Singapore138632 Singapore

ISBN: (纸本)9780791886908

Making use of a large database obtained from high-fidelity CFD simulations of a 5MW NREL wind turbine, we perform an analysis of loading distributions on different sections of the turbine blade and their possible shifts with respect to the change in the operating conditions, i.e. inflow wind speed, rotating speed, tilt and pitch angles. In this paper, we will present a computational fluid dynamics model designed for mass generation of aerodynamic loading data, a finite element analysis structural model for simulating the turbine deformation and stress. Finally, verification of the model, data processing and analysis, and the results of loading and stress distributions on different sections of the turbine blade will be presented. Copyright © 2023 by ASME.

关键词： Finite element method

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Developing a proxy application for an industrial unstructured CFD software: preliminary results 29

Developing a proxy application for an industrial unstructure...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Wang, Qingsong Xu, Chuanfu Zhang, Jian Deng, Liang Dai, Zhe Qiu, Haozhong Dai, Weixi Lin, Yongzhen Ding, Yue Che, Yonggang National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing Changsha China China Aerodynamic Research and Development Center Mianyang China

ISBN: (纸本)9798350330717

As programming models and architectures evolve in the exa-scale era, porting large-scale HPC applications are becoming increasingly difficult and expensive. In HPC community, mini-apps are often developed to mimic real-world applications, and it offers an easy way to benchmark new HPC platforms. In this paper, we design and implement a mini-app MiniFS as a proxy for an industry-level unstructured Computational Fluid Dynamics (CFD) software FlowStar. The main purpose of MiniFS is to evaluate different shared memory approaches on emerging multi/many-core architectures, because data conflicts and data dependencies in unstructured CFD pose tough challenges for shared memory parallelization. Results show that our mini-app can represent the performance characteristic of the original application. However, the existing approaches are unscalable on modern multi/many-cores. It is imperative to develop novel scalable shared memory approaches for unstructured CFD. © 2023 IEEE.

关键词： mini-app shared memory unstructured CFD

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Leveraging the Compute Power of Two HPC Systems for higher-Dimensional Grid-Based Simulations with the Widely-Distributed Sparse Grid Combination Technique 23

Leveraging the Compute Power of Two HPC Systems for Higher-D...

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2023 International Conference for high performance computing, Networking, Storage and Analysis, SC 2023

作者： Pollinger, Theresa Van Craen, Alexander Niethammer, Christoph Breyer, Marcel Pflüger, Dirk Institute for Parallel and Distributed Systems Universität Stuttgart Stuttgart Germany High Performance Computing Center Universität Stuttgart Stuttgart Germany

ISBN: (纸本)9798400701092

Grid-based simulations of hot fusion plasmas are often severely limited by computational and memory resources;the grids live in four- to six-dimensional space and thus suffer the curse of dimensionality. However, high resolutions are required to fully capture the physics of interest. The sparse grid combination technique is a multi-scale method in which many anisotropically coarse resolved grids are used to approximate a fine-scale solution - -and it alleviates the curse of *** paper presents the core concepts of the widely-distributed combination technique, which allows us to use the compute power and memory of more than one HPC system for the same simulation. We apply the sparse grid combination technique to a six-dimensional advection problem serving as a proxy for plasma simulations. The full-grid solution approximated by the combination technique would contain ≈ 5 ZB if computed with conventional grid-based methods. Even the combination technique simulation operates on ≈ 1 × 1011 double-precision degrees of freedom, or 988 GB, plus the supporting sparse grid data structures. We propose a new approach to divide the compute load between the two HPC systems, requiring only 76 GB to be exchanged. Based on this, we have realized the first synchronous combination technique simulation using two HPC systems, in our case the two German Tier-0 supercomputers HAWK and SuperMUC-NG. On two systems, the simulation can be computed at an average overhead of ≈ 35 % (108 s per combination step) for file I/O and transfer. The presented concepts apply to any pair of HPC systems if high-speed data transfer is possible. © 2023 ACM.

关键词： Supercomputers

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Integrating Velox into TinkerPop for Graph Queries on Vectorized Engine 3

Integrating Velox into TinkerPop for Graph Queries on Vector...

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3rd International Conference on Electronic Information Engineering and Computer, EIECT 2023

作者： Li, Zihao Xu, Liyang Jin, Ruochun Chen, Huan Tang, Yuhua National University of Defense Technology Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology Changsha410073 China

ISBN: (纸本)9798350357707

To enhance the query efficiency of relational databases and build a unified computing backend, Meta has developed Velox, a vectorized execution engine library based on columnar storage, Currently, there is no standardized specification for computation engine, and storage in graph databases, leading to failed to effectively utilize the vectorized processing capability of modern CPU. In this paper, we propose a middleware that primarily focuses on (1) non-invasively integrating Velox into the TinkerPop framework to provide unified vectorized engine acceleration for all graph databases supporting the TinkerPop specification;(2) conducting graph queries based on the relational data storage model, eliminating the overhead of transforming the storage model into a graph storage model;(3) validating the acceleration effect of the vectorized engine on interactive workload of graph queries under a single-node environment. © 2023 IEEE.

关键词： Engines

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Decomposition, Interaction, Reconstruction Meets Global Context Learning In Visual Tracking 48

Decomposition, Interaction, Reconstruction Meets Global Cont...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Tan, Huibin Hu, Kun Cao, Mingyu Wang, Mengzhu Xu, Liyang Yang, Wenjing Institute for Quantum Information State Key Laboratory of High Performance Computing China National University of Defense Technology College of Computer Science and Technology Changsha China

ISBN: (纸本)9781728163277

Tensor decomposition and reconstruction attention is a promising global context learning approach because it can remain efficient while avoiding feature compression. To exploit its potential even further in visual tracking, we redesign a 3D tensor modeling paradigm, namely tensor Decomposition, Interaction, Reconstruction attention (DIR), respectively corresponding to three function components, Tensor Decomposition Module (TDM), Tensor Interaction Module (TIM) and Context Reconstruction Module (CRM). Specifically, TDM decomposes a 3D tensor feature into rank-1 context fragments in different dimension views. The ingenuity here lies in the introduction of Circular Convolution for processing features at arbitrary scales and channel-sharing segments to enhance the interaction of the two branches in the Siamese network architecture. TIM obtains the tensor planes of each dimension by the Cross-Similarity operation of rank-1 tensors and fused cubic features, which brings more interactions between all feature dimensions. CRM reconstructs 3D context representations with the outputs of the above modules. In experiments, DIR is embedded into the tracker to verify its effectiveness. © 2023 IEEE.

关键词： context reconstruction Siamese tracking single object tracking tensor plane

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Enhanced Dcf Tracker Regularized by Reliable Sample Construction 48

Enhanced Dcf Tracker Regularized by Reliable Sample Construc...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Hu, Kun Cao, Mingyu Wang, Mengzhu Lan, Long Yang, Wenjing Tan, Huibin Institute for Quantum Information State Key Laboratory of High Performance Computing China National University of Defense Technology College of Computer Science and Technology Changsha China

ISBN: (纸本)9781728163277

Discriminative correlation filter (DCF) is a highly efficient tracking technique using the circulant shifted samples of search images to update the template, so the reliability of input samples determines template quality. In this paper, we rethink the reliability problem of input samples in advance during template updating and propose an enhanced DCF tracking method regularized by a novel sparse representation based reliable sample construction term, called enhanced sparse correlation filter (ESCF). Specifically, the reconstructed reliable samples are the sparse representation of circulant shifted samples of unfiltered input samples, in which the target will approach the center to preserve target visual cues into the template when using the cosine window. Besides, we jointly perform template learning and reliable sample construction into a unified learning paradigm to benefit from each other, which further can be carried out in the frequency domain without incurring excessive time cost by skillful decomposition. Experiments on several popular visual tracking datasets verify the efficacy of ESCF and show that ESCF performs favorably against several well-established representative counterparts. © 2023 IEEE.

关键词： Correlation filter Reliable sample construction Sparse representation Unfiltered features

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Enhancing Medical Diagnosis with Fine-Tuned Large Language Models: Addressing Cardiogenic Pulmonary Edema (CPE) 24

Enhancing Medical Diagnosis with Fine-Tuned Large Language M...

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11th International Conference on Biomedical and Bioinformatics Engineering, ICBBE 2024

作者： Chiu, Yen-Jung Chuang, Chao-Chun Hwa, Kuo-Yuan Department of Biomedical Engineering Ming Chuan University Taipei Taiwan National Center For High-Performance Computing Hsinchu Taiwan Department of Molecular Science and Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9798400718274

Large Language Models (LLMs) have revolutionized natural language processing (NLP) with significant advancements in text generation. LLMs often struggle with complex domain-specific tasks, such as medical report analysis, despite their capabilities. This study focuses on enhancing LLM performance for medical applications, particularly in diagnosing and managing cardiogenic pulmonary edema (CPE). This research explores fine-tuning LLMs to develop a real-time CPE chatbot for Intensive Care Units (ICUs). The chatbot aims to provide diagnostic suggestions and explanations based on patient data. In the results, the LLaMa3-8B model performed better in predicting patients' CPE stage and keyword extraction. The accuracies achieved 72% and 86%. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Diagnosis

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