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proceedings of WORKS 2022: 17th Workshop on Workflows in Support of Large-Scale Science, Held in conjunction with SC 2022: The International Conference for High Performance computing, Networking, Storage and analysis

Proceedings of WORKS 2022: 17th Workshop on Workflows in Sup...

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17th IEEE/acm Workshop on Workflows in Support of Large-Scale Science, WORKS 2022

ISBN: (纸本)9781665451918

The proceedings contain 11 papers. The topics discussed include: challenges of provenance in scientific workflow management systems;a domain-specific composition environment for provenance query of scientific workflows;radical-pilot and Parsl: executing heterogeneous workflows on HPC platforms;workflow anomaly detection with graph neural networks;co-scheduling ensembles of in situ workflows;events as a basis for workflow scheduling;an automated cryo-EM computational environment on the HPC system using Pegasus WMS;cross-facility workflows: case studies with active experiments;and novel proposals for FAIR, automated, recommendable, and robust workflows.

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Conversational Explanations: Discussing Explainable AI with Non-AI Experts 25

Conversational Explanations: Discussing Explainable AI with ...

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30th International Conference on Intelligent User Interfaces, IUI 2025

作者： Zhang, Tong Zhang, Mengao Low, Wei Yan Yang, X. Jessie Li, Boyang Albert College of Computing and Data Science Nanyang Technological University Singapore Singapore Nanyang Technological University Singapore Singapore College of Engineering University of Michigan Ann ArborMI United States

ISBN: (纸本)9798400713064

Explainable AI (XAI) aims to provide insights into the decisions made by AI models. To date, most XAI approaches provide only one-time, static explanations, which cannot cater to users' diverse knowledge levels and information needs. Conversational explanations have been proposed as an effective method to customize XAI explanations. However, building conversational explanation systems is hindered by the scarcity of training data. Training with synthetic data faces two main challenges: lack of data diversity and hallucination in the generated data. To alleviate these issues, we introduce a repetition penalty to promote data diversity and exploit a hallucination detector to filter out untruthful synthetic conversation turns. We conducted both automatic and human evaluations on the proposed system, fEw-shot Multi-round ConvErsational Explanation (EMCEE). For automatic evaluation, EMCEE achieves relative improvements of 81.6% in BLEU and 80.5% in ROUGE compared to the baselines. EMCEE also mitigates the degeneration of data quality caused by training on synthetic data. In human evaluations (N = 60), EMCEE outperforms baseline models and the control group in improving users' comprehension, acceptance, trust, and collaboration with static explanations by large margins. Through a fine-grained analysis of model responses, we further demonstrate that training on self-generated synthetic data improves the model's ability to generate more truthful and understandable answers, leading to better user interactions. To the best of our knowledge, this is the first conversational explanation method that can answer free-form user questions following static explanations. © 2025 Copyright held by the owner/author(s).

关键词： Data assimilation

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Research on Fault Diagnosis Method and Application of Gas Turbine Based on Acoustic Imaging Technology

Research on Fault Diagnosis Method and Application of Gas Tu...

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2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Yan, Wen Hu, Mingliang Wen, Fei Guo, Peipei Guo, Ziang AVIC Shanghai Aviation Measurement & Control Technology Research Institute Shanghai201601 China Xi'an Aeronautics Computing Technique Research Institute AVIC Xi'an710068 China Department of Electronics College of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Aviation Technology for Fault Diagnosis and Health Management Technology Shanghai201601 China

Gas turbine health management is of great significant for enhancing flight safety and reducing maintenance costs. Based on the architecture of gas turbine fault identification system, a multi-arm spiral microphone array with high positioning accuracy, high beam resolution, and strong anti-interference capability is designed in this paper with simulation and experiment. On this basis, by utilizing multi-channel acoustic digital acquisition and analysis equipment, high-precision, wide dynamic range, and high-real-time acquisition of audio data from the combustion chamber of gas turbines are achieved. An audio data analysis strategy based on feature extraction and an autoencoder network construction strategy are proposed, fulfilling the imaging of audio data from the combustion chamber of gas turbines, which can effectively identify gas turbine faults. Experiments conducted on the platform of the multi-arm spiral microphone array indecates that the proposed fault detection strategy has an accuracy rate of over 98%. This is of great theoretical significance and practical value for enhancing the level of gas turbine fault detection, and improving the performance, reliability, and lifespan of gas turbine systems. © The Institution of Engineering & Technology 2024.

关键词： Combustion chambers

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Making Powerful Enemies on NVIDIA GPUs 43

Making Powerful Enemies on NVIDIA GPUs

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43rd IEEE Real-Time systems Symposium (RTSS)

作者： Yandrofski, Tyler Chen, Jingyuan Otterness, Nathan Anderson, James H. Smith, F. Donelson Univ N Carolina Dept Comp Sci Chapel Hill NC 27515 USA

ISBN: (数字)9781665453462

ISBN: (纸本)9781665453462

Graphics Processing Units (GPUs) are widely used in safety-critical real-time systems such as autonomous vehicles due to their high performance on artificial intelligence (AI) workloads. As the computing power of recent GPUs keeps growing, it becomes increasingly possible to allow multiple independent programs to access the GPU concurrently. This complicates timing analysis, as contention for shared GPU resources renders execution times less predictable and worst-case execution times (WCETs) difficult to estimate. This paper provides a method for producing enemy programs that intentionally contend for GPU resources in order to enable more confident measurement-based WCET estimations. This paper provides an experiment-driven method to design effective enemy programs for several different interference channels-specific shared resources within the GPU through which concurrent computations may impact others' execution times. The method is flexible and can be applied to different GPU sharing mechanisms. The enemies are evaluated against a large number of real GPU applications, and the results indicate that these enemies cause higher slowdowns for GPU tasks than other baseline resource-stressing methods.

关键词： real-time systems graphics processing units measurement-based timing analysis interference channels

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Power systems Dynamic State Estimation using Central Difference Filter 2

Power Systems Dynamic State Estimation using Central Differe...

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2nd International Conference on Power, Control and computing Technologies, ICPC2T 2022

作者： Chowdhury, Arindam Chatterjee, Sayantan Dey, Aritro NIT Durgapur Department of Electrical Engineering Durgapur India

ISBN: (纸本)9781665458580

A nonlinear Sigma point Kalman filter known as Central Difference Filter which considers only first order Taylor series approximation with the help of interpolation formula, have been employed here for the first time during dynamic state estimation of power systems states. This paper also exhibits a comparative performance analysis of two estimation techniques namely Central difference filter (CDF) and Cubature Kalman filter technique (CKF) during power systems dynamic state estimation. The estimation is performed employing measurements from Remote terminal units (RTU) and Phasor measurement units (PMU). The whole simulation process is carried out for IEEE 30 bus test system. Holts two parameter linear exponential technique which often utilized as a state forecasting technique has been used here to forecast the systems state at the prediction step. The superiority of CDF over CKF, has been illustrated here on context of computation time and estimation accuracy. © 2022 IEEE.

关键词： Power system dynamics Power control Taylor series Phasor measurement units Power system reliability Performance analysis Kalman filters

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Understanding iOS Privacy Nutrition Labels: An Exploratory Large-Scale analysis of App Store Data

Understanding iOS Privacy Nutrition Labels: An Exploratory L...

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CHI Conference on Human Factors in computing systems (CHI)

作者： Li, Yucheng Chen, Deyuan Li, Tianshi Agarwal, Yuvraj Cranor, Lorrie Hong, Jason I. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450391566

Since December 2020, the Apple App Store has required all developers to create a privacy label when submitting new apps or app updates. However, there has not been a comprehensive study on how developers responded to this requirement. We present the first measurement study of Apple privacy nutrition labels to understand how apps on the U.S. App Store create and update privacy labels. We collected weekly snapshots of the privacy label and other meta-data for all the 1.4 million apps on the U.S. App Store from April 2 to November 5, 2021. Our analysis showed that 51.6% of apps still do not have a privacy label as of November 5, 2021. Although 35.3% of old apps have created a privacy label, only 2.7% of old apps created a privacy label without app updates (i.e., voluntary adoption). Our findings suggest that inactive apps have little incentive to create privacy labels.

关键词： Privacy Privacy Nutrition Label iOS development

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Human Identification Using a Smartphone Motion Sensor and Gait analysis 22

Human Identification Using a Smartphone Motion Sensor and Ga...

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15th acm International Conference on Pervasive Technologies Related to Assistive Environments (PETRA)

作者： Talha, Muhammad Soomro, Hasan Ali Naeem, Nadeem Ali, Ehsan Kyrarini, Maria Quaid E Awam Univ Engn Sci & Technol Dept Elect Engn Nawabshah Pakistan Santa Clara Univ Dept Elect & Comp Engn Santa Clara CA USA

ISBN: (纸本)9781450396318

This research focuses on the modeling of human gait in order to recognize a human by their walking style. Gait analysis is a very important parameter, especially for biometric systems and also for healthcare applications. In this research, human gait is captured by using only a single Inertial measurement Unit (IMU) sensor, which is positioned on top of the ankle. MATLAB mobile application is used to access the IMU sensor. A small study of 30 participants was conducted and two databases are then developed with different features. The first database contains only IMU sensor data, while the second database contains information on the height and gender of each participant. Both databases are used to train and test four different machine learning algorithms and their performances are compared. The experimental results show that the acquired setup performs well for classification purposes. Results from both databases are comparable and provide sufficient accuracy in the recognition task.

关键词： Gait analysis Inertial measurement Unit (IMU) Machine Learning Human Motion analysis Motion Sensors

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RAVIC: Runtime analysis Visualizer for Introductory Courses 2023

RAVIC: Runtime Analysis Visualizer for Introductory Courses

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54th Annual acm SIGCSE Technical Symposium on Computer Science Education (SIGCSE TS)

作者： Haldeman, Georgiana Pizer, Emma Hou, Mathelide Rojas, Matt Han, Kevin Kamran, Ahmed Colgate Univ Hamilton NY 13346 USA

ISBN: (纸本)9781450394338

As the global economy's demand for computer applications soars, the demand for well-trained computer science (CS) professionals is rising. This trend fuels a surge in CS undergraduate degree production which, in turn, puts a strain on departmental resources. In addition, CS departments have to contend with high dropout and failure rates, fragile learning and bimodal outcomes [1]. Thus, the need for effective teaching techniques in CS education is greater than ever. Some concepts and skills in CS are very difficult to acquire such as analyzing the running time of short pieces of code [2], and particularly, computing the running time of loops. Most instructors use a trace-sum-approximate flow chart described in [2] to teach students how to analyze the running time of code. The two most important skills in this analysis process are the tracing of code and the approximation of the sum of different number patterns, e.g. the sum of the linear number pattern 1 + 2 + 3 +... + n is equal to n*(n+1)/2 and it is approximated to O(n(2)). Novice programmers struggle with both these integral skills [3, 4]. Visual systems have been recognized to improve students' understanding of these concepts [4]. Several tools have been developed to assist students with running time analysis. Existing tools are targeted at students with more advanced training, such as a background in advanced data structures (AAV [4]) or experience with code tracing and approximation of the sum of different number patterns (Compigorithm [5]). However, none of the existing tools teach students how to compute the running time at the introductory level, and this gap presented a unique opportunity for us. An effective run-time analysis visualization system for introductory courses must depict the tracing and approximation of the sum. We propose a design in which the depiction of the loop tracing for run-time analysis is done through the use of a table, where the columns represent loop variables and each row represe

关键词： visualization time complexity runtime analysis code tracing

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"I spent 14 hours debugging just one assignment": Toward Computer-Mediated Personal Informatics for Computer Science Student Mental Health 25

"I spent 14 hours debugging just one assignment": Toward Com...

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Chandrasekaran, Aishwarya Bielicke, London Shah, Diya Janakiraman, Harisha Mauriello, Matthew Louis Computer and Information Sciences University of Delaware NewarkDE United States Computer Science Rhodes College MemphisTN United States Accounting & Management Information Systems University of Delaware NewarkDE United States

ISBN: (纸本)9798400713941

Anxiety and depression rates in Computer Science (CS) students are double those of other undergraduates and 5-10 times higher than the general population. However, factors contributing to the elevated mental health issues in CS students remain unknown. To bridge this gap, we conducted need-finding interviews (N=20), which revealed that the complexity of debugging, along with imposter syndrome, are key contributors to stress and burnout. Participants expressed openness toward and feature preferences in a computer-based Personal Informatics (PI) tool to facilitate self-reflection. In response, we developed EmotionStream, an algorithm-assisted PI tool that provides both contextual and emotional insights based on individual behaviors. We found that participants rated their experience with the tool highly. Post-hoc analysis revealed that emotional states, augmented with contextual cues, show promise of predicting real-time stress. Based on our findings, we provide design implications for future PI tools to support CS student mental well-being. © 2025 Copyright held by the owner/author(s).

关键词： student

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The First 5G-LTE Comparative Study in Extreme Mobility 22

The First 5G-LTE Comparative Study in Extreme Mobility

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2022 acm SIGMETRICS/IFIP PERFORMANCE Joint International Conference on measurement and Modeling of Computer systems, SIGMETRICS/PERFORMANCE 2022

作者： Pan, Yueyang Li, Ruihan Xu, Chenren Peking University Beijing China

ISBN: (纸本)9781450391412

5G claims to support mobility up to 500 km/h according to the 3GPP standard. However, its field performance under high-speed scenes remains in mystery. In this paper, we conduct the first large-scale measurement campaign on a high-speed railway route operating at the maximum speed of 350 km/h, with full coverage of LTE and 5G (NSA and SA) along the track. Our study consumed 1788.8 GiB of cellular data in six months, covering the three major carriers in China and the recent standardized QUIC protocol. Based on our dataset, we reveal the key characteristics of 5G and LTE in extreme mobility in terms of throughput, RTT, loss rate, signal quality, and physical resource utilization. We further develop a taxonomy of handovers in both LTE and 5G and carry out the link-layer latency breakdown analysis. Our study pinpoints the deficiencies in the user equipment, radio access network, and core network which hinder seamless connectivity and better utilization of 5G's high bandwidth. Our findings highlight the directions of the next step in the 5G evolution. © 2022 Owner/Author.

关键词： high-speed rail extreme mobility handover measurement 5g

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