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2nd IEEE International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2023

作者： Pradhan, Somalika Brahma, Biswajit Pramanik, Jitendra Centurion University of Technology and Management Odisha India Senior Data & Visualization Engineer McKesson Corporation United States National Institute of Technology Department of Mining Odisha Rourkela India

ISBN: (纸本)9798350381979

In this investigation, the BIOVIA material studio was used to evaluate the PAN/PEG composite. The composite's thermal conductivity and heat capacity were measured, and the root mean square error was predicted using the ANN model in the Synthia module of the BIOVIA application. The composite's thermal conductivity and heat capacity were evaluated throughout a range of polyethylene glycol mass fractions, from 0% to 1%. Compared to the pure material, the composite's thermal conductivity increased by 46%, and its heat capacity increased by 9.4% when PEG made up 1% of the mass fraction. Thermal conductivity and heat capacity data were taken in a dry laboratory and then analyzed using a bi-layer artificial neural network (ANN). The ANN's thermal conductivity and heat capacity estimates held up throughout testing. The implemented ANN modeled Both attributes well, with a Mean Squared Log Error of 1.29 and 14.46, respectively © 2023 IEEE.

关键词： Specific heat

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Deliberative XAI: How Explanations Impact Understanding and Decision-Making of AI Novices in Collective and Individual Settings

arXiv

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arXiv 2024年

作者： Schmude, Timothée Koesten, Laura Möller, Torsten Tschiatschek, Sebastian University of Vienna Faculty of Computer Science Research Network Data Science Doctoral School Computer Science Austria University of Vienna Faculty of Computer Science Research Group Visualization and Data Analysis Austria University of Vienna Faculty of Computer Science Research Group Visualization and Data Analysis Research Network Data Science Austria University of Vienna Faculty of Computer Science Research Network Data Science Research Group Data Mining and Machine Learning Austria

XAI research often focuses on settings where people learn about and assess algorithmic systems individually. However, as more public AI systems are deployed, it becomes essential for XAI to facilitate collective understanding and deliberation. We conducted a task-based interview study involving 8 focus groups and 12 individual interviews to explore how explanations can support AI novices in understanding and forming opinions about AI systems. Participants received a collection of explanations organized into four information categories to solve tasks and decide about a system’s deployment. These explanations improved or calibrated participants’ self-reported understanding and decision confidence and facilitated group discussions. Participants valued both technical and contextual information and the self-directed and modular explanation structure. Our contributions include an explanation approach that facilitates both individual and collaborative interaction and explanation design recommendations, including active and controllable exploration, different levels of information detail and breadth, and adaptations to the needs of decision subjects. Copyright © 2024, The Authors. All rights reserved.

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Prediction of Thermal Conductivity and Heat Capacity of PAN and PEG Copolymers Composite using Artificial Neural Network

Prediction of Thermal Conductivity and Heat Capacity of PAN ...

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Industrial Electronics: Developments & Applications (ICIDeA), IEEE International Conference on-

作者： Somalika Pradhan Biswajit Brahma Jitendra Pramanik Centurion University of Technology and Management Odisha India Senior Data & Visualization Engineer McKesson Corporation USA Department of Mining National Institute of Technology Rourkela Odisha

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Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making

arXiv

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arXiv 2023年

作者： Schmude, Timothée Koesten, Laura Möller, Torsten Tschiatschek, Sebastian University of Vienna Faculty of Computer Science Research Network Data Science UniVie Doctoral School Computer Science DoCS Austria University of Vienna Faculty of Computer Science Research Group Visualization and Data Analysis Austria University of Vienna Faculty of Computer Science Research Network Data Science Research Group Visualization and Data Analysis Austria University of Vienna Faculty of Computer Science Research Network Data Science Research Group Data Mining and Machine Learning Austria

We argue that explanations for "algorithmic decision-making" (ADM) systems can profit by adopting practices that are already used in the learning sciences. We shortly introduce the importance of explaining ADM systems, give a brief overview of approaches drawing from other disciplines to improve explanations, and present the results of our qualitative task-based study incorporating the "six facets of understanding" [24] framework. We close with questions guiding the discussion of how future studies can leverage an interdisciplinary approach. © 2023, CC BY.

关键词： Decision making

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On the Impact of Explanations on Understanding of Algorithmic Decision-Making

arXiv

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arXiv 2023年

Ethical principles for algorithms are gaining importance as more and more stakeholders are affected by "high-risk" algorithmic decision-making (ADM) systems. Understanding how these systems work enables stakeholders to make informed decisions and to assess the systems’ adherence to ethical values. Explanations are a promising way to create understanding, but current explainable artificial intelligence (XAI) research does not always consider existent theories on how understanding is formed and evaluated. In this work, we aim to contribute to a better understanding of understanding by conducting a qualitative task-based study with 30 participants, including users and affected stakeholders. We use three explanation modalities (textual, dialogue, and interactive) to explain a "high-risk" ADM system to participants and analyse their responses both inductively and deductively, using the "six facets of understanding" framework by Wiggins & McTighe [63]. Our findings indicate that the "six facets" framework is a promising approach to analyse participants’ thought processes in understanding, providing categories for both rational and emotional understanding. We further introduce the "dialogue" modality as a valid explanation approach to increase participant engagement and interaction with the "explainer", allowing for more insight into their understanding in the process. Our analysis further suggests that individuality in understanding affects participants’ perceptions of algorithmic fairness, demonstrating the interdependence between understanding and ADM assessment that previous studies have outlined. We posit that drawing from theories on learning and understanding like the "six facets" and leveraging explanation modalities can guide XAI research to better suit explanations to learning processes of individuals and consequently enable their assessment of ethical values of ADM systems. © 2023, CC BY.

关键词： Decision making

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Visualizing the Evolution of Groups of Politicians Mentioned in the News

Visualizing the Evolution of Groups of Politicians Mentioned...

引用

International Conference on Information Visualisation (IV)

作者： Carolina Bento Daniel Gonçalves Bruno Martins Instituto Superior Técnico Universidade de Lisboa INESC-ID Data Mining and Information Retrieval Group INESC-ID Visualization and Intelligent Multimodal Interfaces Group

In this paper, we describe a tool to visualize and explore communities of politicians arising from mentions in news articles, combining techniques from network analysis and visual analytics. With this tool one can explore the communities, their organization according to parties, with whom a politician was mentioned with in a given year, or key political events, like the emergence of a new prime-minister. User tests involving our tool, and a collection of Portuguese news articles for a period of 10 years, have shown the interest on this kind of tool, and its applicability to analyze group evolution.

关键词： Communities data visualization Peer-to-peer computing Visual analytics Organizations Media

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Monitoring Network Traffic with Radial Traffic Analyzer

Monitoring Network Traffic with Radial Traffic Analyzer

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IEEE Symposium on Visual Analytics Science and Technology (VAST)

作者： Daniel A. Keim Florian Mansmann Jorn Schneidewind Tobias Schreck Databases Data Mining and Visualization Group University of Konstanz Germany

Extensive spread of malicious code on the Internet and also within intranets has risen the user's concern about what kind of data is transferred between her or his computer and other hosts on the network. Visual analysis of this kind of information is a challenging task, due to the complexity and volume of the data type considered, and requires special design of appropriate visualization techniques. In this paper, we present a scalable visualization toolkit for analyzing network activity of computer hosts on a network. The visualization combines network packet volume and type distribution information with geographic information, enabling the analyst to use geographic distortion techniques such as the HistoMap technique to become aware of the traffic components in the course of the analysis. The presented analysis tool is especially useful to compare important network load characteristics in a geographically aware display, to relate communication partners, and to identify the type of network traffic occurring. The results of the analysis are helpful in understanding typical network communication activities, and in anticipating potential performance bottlenecks or problems. It is suited for both off-line analysis of historic data, and via animation for on-line monitoring of packet-based network traffic in real time

关键词： Telecommunication traffic Information analysis data visualization Computer networks Computerized monitoring IP networks Displays Performance analysis data analysis Animation

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Real time change detection and alerts from highway traffic data 05

Real time change detection and alerts from highway traffic d...

引用

ACM/IEEE 2005 Supercomputing Conference, SC'05

作者： Grossman, Robert Sabala, Michal Aanand, Anushka Eick, Steve Wilkinson, Leland Zhang, Pei Chaves, John Vejcik, Steve Dillenburg, John Nelson, Peter Rorem, Doug Alimohideen, Javid Leigh, Jason Papka, Mike Stevens, Rick National Center for Data Mining University of Illinois Chicago Open Data Research Department of Computer Science University of Illinois Chicago Electronic Visualization Laboratory University of Illinois Chicago Argonne National Laboratory

ISBN: (纸本)1595930612

We developed a testbed containing: real time data from over 830 highway traffic sensors in the Chicago region, data about weather, and text data about events that might affect traffic. The goal was to detect in real time interesting changes in traffic conditions. Given the size and complexity of the data, we choose to build a large number of separate baseline models. We built a separate baseline for each hour in the day, for each day in the week, and for every 2 or 3 traffic sensors, resulting in over 42,000 separate baseline models. We also built a baseline engine to build the necessary baselines automatically. We modified an open source scoring engine to process in real time each new sensor reading, update the appropriate feature vectors, score the updated feature vectors using the baseline models, and send out real time alerts when deviations from the baselines were detected. © 2005 IEEE.

关键词： Real time systems

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A methodology for supporting collaborative exploratory analysis of massive data sets in tele-immersive environments

A methodology for supporting collaborative exploratory analy...

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International Symposium on High Performance Distributed Computing

作者： J. Leigh A.E. Johnson T.A. DeFanti S. Bailey R. Grossman Electronic Visualization Laboratory University of Illinois Chicago USA National Center for Data Mining

This paper proposes a methodology for employing collaborative, immersive virtual environments as a high-end visualization interface for massive data-sets. The methodology employs feature detection, partitioning, summarization and decimation to significantly cull massive data-sets. These reduced data-sets are then distributed to the remote CAVEs, ImmersaDesks and desktop workstations for viewing. The paper also discusses novel techniques for collaborative visualization and meta-data creation.

关键词： Collaboration data analysis data visualization Collaborative work data mining Rendering (computer graphics) Virtual environment Humans US Department of Energy Physics computing

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A review of tele-immersive applications in the CAVE research network

A review of tele-immersive applications in the CAVE research...

引用

IEEE Annual International Symposium Virtual Reality

作者： J. Leigh A.E. Johnson T.A. DeFanti M. Brown M.D. Ali S. Bailey A. Banerjee P. Benerjee Jim Chen K. Curry J. Curtis F. Dech B. Dodds I. Foster S. Fraser K. Ganeshan D. Glen R. Grossman R. Heiland J. Hicks A.D. Hudson T. Imai M.A. Khan A. Kapoor R.V. Kenyon J. Kelso R. Kriz C. Lascara X. Liu Y. Lin T. Mason A. Millman K. Nobuyuki K. Park B. Parod P.J. Rajlich M. Rasmussen M. Rawlings D.H. Robertson S. Thongrong R.J. Stein K. Swartz S. Tuecke H. Wallach Hong Yee Wong G.H. Wheless National Center for Supercomputing Applications University슠of슠Illinois Urbana-Champaign USA Electronic Visualization Laboratory University of Illinois Chicago USA National Center for Data-Mining University of Illinois Chicago USA Industrial Virtual Reality Laboratory University of Illinois Chicago USA Northwestern University USA Virginia Tech Antenna Group USA Searle Argonne National Laboratory USA Purdue University Indiana University USA Center for Coastal Physical Oceanography Old Dominion University USA Institute of High Performance Computing National University of Singapore Singapore Virtual Reality in Medicine Laboratory University of Illinois Chicago USA Tohwa University Japan

This paper presents an overview of the tele-immersion applications that have been built by collaborators around the world using the CAVERNsoft toolkit, and the lessons learned from building these applications. In particular the lessons learned are presented as a set of rules-of-thumb for developing tele-immersive applications in general.

关键词： Intelligent networks Laboratories visualization Virtual reality Collaborative work Virtual environment Image databases Industrial training Computer networks Sea measurements

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