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IEEE Aerospace conference (AERO)

作者： Bradford, Emma Kokorowski, Michael Lawrence, David Cullinan, Joe CALTECH Jet Prop Lab 4800 Oak Grove Dr Pasadena CA 91109 USA John Hopkins Appl Phys Lab 11100 Johns Hopkins Rd Laurel MD 20723 USA Maxar Technol 3875 Fabian Way Palo Alto CA 94303 USA

ISBN: (数字)9781665437608

ISBN: (纸本)9781665437608

(16) Psyche is a metallic asteroid located in the asteroid belt between Mars and Jupiter. The composition of Psyche is unknown, but the scientific community believes it is composed primarily of iron, nickel, and silicates. The Psyche mission will be the first space mission to study this asteroid in close proximity, and as such, determining the elemental composition of the asteroid is one of the primary objectives of this mission. The spacecraft measures this elemental composition using the Gamma Ray Spectrometer (GRS), which detects cosmic-ray induced gamma rays from Psyche's surface. In addition to gamma rays from Psyche, the GRS will also detect background gamma rays from spacecraft material nearby the GRS. Because understanding the asteroid's Ni composition is a key to achieving the mission science objectives, a special effort has been made to minimize background gamma rays from Ni on spacecraft material, thus maximizing sensitivity to the Ni gamma rays from Psyche. The Psyche mission approached this potential Ni background issue with two methods;i) locating the GRS away from the spacecraft/source of Ni and ii) setting a threshold requirement against the total Ni mass of the spacecraft. Verifying that the total amount of Ni on the spacecraft is within this threshold is thus crucial to ensure the GRS can meet its science objectives. Ni alloys are commonly used on spacecraft, but the mass and location of elemental Ni is not typically accounted for. Ni can be found in many materials all over the spacecraft - in fasteners, optical assemblies, magnetic shields, electromagnetic interference (EMI) tape, under gold plating, in connectors, and so on. Ni accounting proved further challenging because of the distributed nature of the spacecraft build and the use of vendors external to JPL. While the analysis was atypical and source information difficult to cull, the approach described in this paper used tools and data available to the project in some form to achieve this goa

关键词： materials science nickel Psyche space exploration

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New Paradigm in Postural Control Response: A Dual Approach Using Center of Pressure and Electroencephalography

New Paradigm in Postural Control Response: A Dual Approach U...

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E-Health and Bioengineering conference (EHB)

作者： Vittorio Santoriello Lorena Guerrini Federica Pescaglia Marco Recenti Ida Maruotto Carmine Gelormini Carlo Ricciardi Alfonso Maria Ponsiglione Maria Romano Francesco Amato Paolo Gargiulo Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy Institute of Biomedical and Neural Engineering Reykjavik University Reykjavik Iceland Department of Mathematics Physics and Engineering Applications University of Campania L. Vanvitelli Caserta Italy

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

The assessment of Postural Control (PC) is crucial for identifying balance deficits, understanding the underlying mechanisms of instability, and guiding targeted interventions. One widely used approach to evaluate PC involves analyzing both the Center of Pressure (CoP) and Electroencephalography (EEG) data. This study aims to investigate differences in PC responses between genders and age groups (Over40 and Under 40) through the analysis of CoP and EEG across different experimental phases designed to evoke PC strategies. The BioVRSea bio-measurement system, which combines virtual reality (VR) and a mobile platform, was used to assess these differences. The CoP analysis revealed statistically significant differences between genders, particularly during transitions from dynamic visual stimuli to static visual conditions. Men exhibited greater sway than women, indicating a higher susceptibility to habituation phenomena. EEG power comparisons across frequency bands (Delta, Theta, Alpha, Beta, and Low Gamma) showed that the Beta and Low Gamma bands consistently differentiated between the sexes, with males exhibiting higher power levels than females. When comparing age groups, significant results were observed during the phases with only visual stimuli (PRE and POST). Subjects over 40 displayed greater sway during these phases, suggesting a deterioration in vestibular and proprioceptive function. EEG analysis revealed that the Theta band consistently showed the most significant age-related differences across all experimental phases. These findings are valuable for predicting fall risk, particularly with age-related decline, and provide insights into the influence of visual, vestibular, and somatosensory systems on PC. Additionally, the results contribute to understanding anatomical factors involved in responses to multiple stimuli, as postural patterns may indicate underlying pathologies.

关键词： Somatosensory visualization Pathology Propioception Virtual reality Electroencephalography Biomedical engineering

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Multi-Objective Evolutionary Algorithms for Hardware Design Space exploration

Multi-Objective Evolutionary Algorithms for Hardware Design ...

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Innovative Practices in Technology and Management (ICIPTM), International conference on

作者： Rahul Kumar Monit Kapoor Neeraj Varshney Anurag Shrivastava Manish Saraswat Devendra Singh Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India Centre of Research Impact and Outreach Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab Department of Computer Engineering and Applications GLA University Mathura Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu Lloyd Institute of Engineering & Technology Greater Noida Department of Computer Science & Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

This work investigates the use of Multi-Objective Evolutionary Algorithms (MOEAs) in the Hardware Design Space exploration context. Through the use of a heterogeneous data set that spanned different hardware configurations and performance measurements, four widely known MOEAs namely NSGA-ii, SPEA2 IBEA MOPSO have been systematically assessed. Experiments have been aimed at major indicators, including convergence, diversity, and hypervolume maximization. It has been shown that NSGA-ii and SPEA2 have been largely well-balanced in terms of convergence versus diversity, a feature that makes them suitable options for the optimization task. IBEA has been best in hypervolume maximization, which indicates that it is a powerful method when applied to scenarios where extensive coverage of the design space needs to be achieved. MOPSO, using the ideas from particle swarm optimization, gave a solid competitor that featured excellent convergence and diversity. This work also does a comparative study with related works, which shows the generality of MOEAs in different domains such as facility location optimization, system design and control theory robotics bioinformatics computer vision, and networked systems. The research provides relevant inputs to help researchers and practitioners choose the best algorithms for hardware design optimization, which includes considering specific goals and constraints. Consequently, the research shows us how this way and a method of creation.

关键词： Technological innovation Solids Hardware Space exploration Particle swarm optimization Bioinformatics Task analysis

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SPLORT: Evaluation of a Web-based Approach for Descriptive and Exploratory analysis of Multivariate Spatio-temporal data 21

SPLORT: Evaluation of a Web-based Approach for Descriptive a...

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14th International Symposium on visual Information Communication and Interaction, VINCI 2021

作者： Feijóo-García, Miguel Alfonso Hernández-Peñalosa, José Tiberio Program of Systems and Computing Engineering Universidad de Los Andes Colombia and Program of Systems Engineering Universidad El Bosque Colombia Program of Systems and Computing Engineering Universidad de Los Andes Colombia

ISBN: (纸本)9781450386470

The multivariate Spatiooral data challenges the analysts along the navigation and exploration of the information, using data Analytics techniques. We present SPLORT, as a user-centered web-based solution for segmented visual Analytics. The tool involves a "What-Where-When"pyramidal paradigm to drive Spatiooral analysis towards the findings of new insights. It features multi-layered coordinated views to help the analyst navigate and explore multivariate data simultaneously. We evaluated this web-based tool, and reported the findings and results, considering users' performance and perceptions, basing our analysis on their Likert scale (0-5) responses, regarding their experience and the tool's usability, and the sentiment of their feedback, by using Natural Language Processing (NLP) techniques. Our findings from the pilot study held, suggest that SPLORT successfully allows the users to visually query, explore and analyze contextless multi-scale attributes within space and time, which quickly drives them to new insights and to support easier decision-making processes. Moreover, the tool's flexibility, due to its multi-layered GUI, supports better and more friendly visual analytics. © 2021 ACM.

关键词： data Analytics

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Affection: Learning Affective Explanations for Real-World visual data

Affection: Learning Affective Explanations for Real-World Vi...

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Panos Achlioptas Maks Ovsjanikov Leonidas Guibas Sergey Tulyakov Snap Inc. Stanford University LIX Ecole Polytechnique IP Paris

In this work, we explore the space of emotional reactions induced by real-world images. For this, we first introduce a large-scale dataset that contains both categorical emotional reactions and free-form textual explanations for 85,007 publicly available images, analyzed by 6,283 annotators who were asked to indicate and explain how and why they felt when observing a particular image, with a total of 526,749 responses. Although emotional reactions are subjective and sensitive to context (personal mood, social status, past experiences) - we show that there is significant common ground to capture emotional responses with a large support in the subject population. In light of this observation, we ask the following questions: i) Can we develop neural networks that provide plausible affective responses to real-world visual data explained with language? ii) Can we steer such methods towards producing explanations with varying degrees of pragmatic language, justifying different emotional reactions by grounding them in the visual stimulus? Finally, iii) How to evaluate the performance of such methods for this novel task? In this work, we take the first steps in addressing all of these questions, paving the way for more human-centric and emotionally-aware image analysis systems. Our code and data are publicly available at https://***.

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Exploratory analysis of Zero-Shot Lunar Crater Detection using SAM for Chandrayaan-2 Images

Exploratory Analysis of Zero-Shot Lunar Crater Detection usi...

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Communication, Control and Intelligent Systems (CCIS)

作者： Kaustubh Koranglekar Prateek K Shankar Kumar Dheeraj Kumar Biswas Nitin Khanna Department of Mechatronics Indian Institute of Technology Bhilai (IIT Bhilai) Bhilai India Department of Electrical Engineering Indian Institute of Technology Bhilai (IIT Bhilai) Bhilai India Department of Computer Science and Engineering Indian Institute of Technology Bhilai (IIT Bhilai) Bhilai India

ISBN: (数字)9798331528201

ISBN: (纸本)9798331528218

This paper explores the application of a zero-shot lunar crater detection method based on the Segment Anything Model (SAM) for high-resolution Digital Terrain Model (DTM) images from ISRO’s Chandrayaan-ii mission. A pre-trained transformer-based instance segmentation model, SAM, is used to segment and identify lunar craters without requiring training data. The proposed method is capable of detecting craters in varying crater sizes and shapes, highlighting its potential for generalizable planetary feature detection. This work investigates the applicability of general-purpose deep learning models in planetary exploration and offers insights for efficient lunar surface analysis.

关键词： Instance segmentation Deep learning Analytical models Shape Feature detection Moon Training data Transformers Intelligent systems Digital elevation models

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Deep learning in the ultrasound evaluation of neonatal respiratory status 25

Deep learning in the ultrasound evaluation of neonatal respi...

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25th International conference on Pattern Recognition (ICPR)

作者： Gravina, Michela Gragnaniello, Diego Verdoliva, Luisa Poggi, Giovanni Corsini, Iuri Dani, Carlo Meneghin, Fabio Lista, Gianluca Aversa, Salvatore Raimondi, Francesco Migliaro, Fiorella Sansone, Carlo Univ Naples Federico II Dept Elect Engn & Informat Technol Naples Italy Univ Naples Federico II Dept Ind Engn Naples Italy Univ Naples Federico II Dept Translat Med Sci Div Neonatol Sect Pediat Naples Italy Hosp Careggi Florence Florence Italy Hosp Vittore Buzzi Milan Italy Civil Hosp Brescia Brescia Italy

ISBN: (纸本)9781728188089

Lung ultrasound imaging is reaching growing interest from the scientific community. On one side, thanks to its harmlessness and high descriptive power, this kind of diagnostic imaging has been largely adopted in sensitive applications, like the diagnosis and follow-up of preterm newborns in neonatal intensive care units. On the other side, state-of-the-art image analysis and pattern recognition approaches have recently proven their ability to fully exploit the rich information contained in these data, making them attractive for the research community. In this work, we present a thorough analysis of recent deep learning networks and training strategies carried out on a vast and challenging multicenter dataset comprising 87 patients with different diseases and gestational ages. These approaches are employed to assess the lung respiratory status from ultrasound images and are evaluated against a reference marker. The conducted analysis sheds some light on this problem by showing the critical points that can mislead the training procedure and proposes some adaptations to the specific data and task. The achieved results sensibly outperform those obtained by a previous work, which is based on textural features, and narrow the gap with the visual score predicted by the human experts.

关键词： Diagnosis

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A Pipeline for Immersive data visualization in CAVE Systems

A Pipeline for Immersive Data Visualization in CAVE Systems

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Challa, Koundinya Jaiswal, Chandra Pendem, Abhinav Gokaraju, Balakrishna North Carolina A&T State University Dept. Computational Data Science and Engineering Greensboro United States

ISBN: (纸本)9798331504847

Virtual Reality (VR) has transformed data visualization by enabling immersive and interactive experiences. CAVE (Cave Automatic Virtual Environment) systems provide a unique platform for exploring complex datasets in an intuitive, spatially immersive manner. However, a standardized pipeline for developing VR scripts tailored to CAVE-based data visualization remains underexplored. This paper presents a structured pipeline for creating and deploying immersive data visualization in CAVE systems, specifically using the WorldViz Prism CAVE environment. Our approach facilitates seamless integration of multi-dimensional datasets, enabling real-time interaction with 27 visual graphs within a single VR scene. The system allows dynamic graph manipulation, interactive exploration, and enhanced user engagement. By streamlining VR script development, this pipeline improves accessibility for researchers and practitioners, fostering a more intuitive understanding of complex datasets. Experimental results demonstrate the effectiveness of this approach in enhancing data interpretability and decision-making. © 2025 IEEE.

关键词： Video analysis

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Research on the Application Algorithm of Multimodal Learning in GPT Large Model

Research on the Application Algorithm of Multimodal Learning...

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IEEE International conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Xinhui Guo Jiasheng Zhang Ying Ren Yulai Ling Huiming Tang Polytechnic Institute Zhejiang University Hangzhou China Innovation Institute Huaxin Consulting Co. Ltd Hangzhou China College of Information Science & Electronic Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350389418

ISBN: (纸本)9798350389425

This paper discusses the research on the application algorithm of multimodal learning based on the GPT model. Combined with the Transformer architecture, a cross-modal alignment algorithm is proposed to optimize the deep fusion of text and visual information. By introducing the generative adversarial network (GAN), the generation and conversion capabilities of multimodal data are further improved, and efficient collaboration between different modalities is achieved. In the system design, the multimodal data is first preprocessed, and then feature extraction and information aggregation are performed through the encoder and decoder structure based on the Transformer. Then, the cross-modal alignment algorithm is used to match and convert the features of different modal data. In the final stage, the performance of the architecture is improved by strengthening the adversarial generative network, aiming to enhance the system’s performance in dealing with complex cross-modal tasks. This study selected a series of public databases for testing. The actual test results show that the proposed technology has shown significant improvements in topics such as image text creation and image category judgment. For the image-to-text synthesis task, the matching rate between the output text and the calibrated image increased by 15.7%. For the image category classification task, the judgment accuracy increased by 12.4%. The experimental evidence has conclusively proved that this text technology has substantial effects in the field of cross-media learning, opening a new perspective for the subsequent in-depth exploration of cross-media learning principles.

关键词： visualization Accuracy Generative adversarial networks Transformers data models Stability analysis Classification algorithms System analysis and design Image classification Testing

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Transactional Panorama: A Conceptual Framework for User Perception in Analytical visual Interfaces

arXiv

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arXiv 2023年

作者： Tang, Dixin Fekete, Alan Gupta, Indranil Parameswaran, Aditya G. UC Berkeley United States The University of Sydney Australia University of Illinois Urbana-Champaign United States

Many tools empower analysts and data scientists to consume analysis results in a visual interface. When the underlying data changes, these results need to be updated, but this update can take a long time-all while the user continues to explore the results. Tools can either (i) hide away results that haven't been updated, hindering exploration;(ii) make the updated results immediately available to the user (on the same screen as old results), leading to confusion and incorrect insights;or (iii) present old-and therefore stale-results to the user during the update. To help users reason about these options and others, and make appropriate trade-offs, we introduce Transactional Panorama, a formal framework that adopts transactions to jointly model the system refreshing the analysis results and the user interacting with them. We introduce three key properties that are important for user perception in this context: visibility (allowing users to continuously explore results), consistency (ensuring that results presented are from the same version of the data), and monotonicity (making sure that results don't "go back in time"). Within transactional panorama, we characterize all feasible property combinations, design new mechanisms (that we call lenses) for presenting analysis results to the user while preserving a given property combination, formally prove their relative orderings for various performance criteria, and discuss their use cases. We propose novel algorithms to preserve each property combination and efficiently present fresh analysis results. We implement our framework into a popular, open-source BI tool, illustrate the relative performance implications of different lenses, and demonstrate the benefits of the novel lenses and our optimizations. © 2023, CC BY.

关键词： Economic and social effects

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