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作者： Moreira, Catarina Simoes, Francisco P. M. Lee, Mark J. W. Zorzal, Ezequiel R. Lindeman, Robert W. Pereira, Joao Madeiras Johnsen, Kyle Jorge, Joaquim Queensland University of Technology School of Information Systems BrisbaneQLD4000 Australia Universidade Federal Rural de Pernambuco Departamento de Computação Recife52171-900 Brazil La Trobe University Computer Science and Information Technology BundooraVIC3086 Australia University of Canterbury HIT Lab NZ Christchurch8041 New Zealand Instituto Superior Técnico Universidade de Lisboa INESC-ID Department of Computer Science and Engineering Lisboa1000-029 Portugal University of Georgia School of Electrical and Computer Engineering AthensGA30602 United States

The pandemic brought about an unprecedented number of virtual conferences, given the heavy restrictions on travel to in-person meetings. Despite all the advances in technology, people still complain about virtual events. There is Zoom fatigue, confinement malaise, and a longing for personal social interactions. This paper discusses our experience organizing the IEEE Virtual Reality Conference (IEEE VR) as a virtual event. IEEE VR was a success with 1200+ registered paying participants, dozens of workshops and tutorials, and hundreds of technical papers. We used (1) a virtual environment platform, together with (2) discussion tools and (3) videoconferencing/broadcast/online tools to further provide effective social interaction and increase engagement. In this paper, we explore the synergies between virtual environments and other online tools and assess user engagement by analyzing the messages exchanged between participants across different genders and geographical regions. To this end, we apply diverse engagement metrics for online conferences. Our analysis shows that these metrics have the potential to highlight engagement, diversity, and inclusion by combining textual messages, participant geographic and gender information, communities of participants, and visitation patterns in a virtual environment. Drawing on our results and experiences, we propose guidelines for organizing technical virtual events to increase diversity and social interaction. © 2013 IEEE.

关键词： Virtual reality

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Effortless In-Vehicle Task-Oriented Dialogue: Enhancing Natural and Efficient Interactions

Effortless In-Vehicle Task-Oriented Dialogue: Enhancing Natu...

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2025 CHI Conference on Human Factors in Computing systems, CHI EA 2025

作者： Du, Huifang Li, Shuqin Dai, Yi Wang, Haofen College of Design and Innovation Tongji University Shanghai China School of Computer Science Hangzhou Dianzi University Information Engineering School Zhejiang Hangzhou China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

ISBN: (纸本)9798400713958

Have you ever struggled to give commands to your in-vehicle assistant? Have you stopped using it because of the lengthy, multi-turn dialogues? In-vehicle Task-Oriented Dialogue (TOD) systems often require detailed instructions and multiple interaction turns, increasing cognitive load, distracting drivers, and causing frustration. To address this, we propose a human-centered, efficient approach to in-vehicle TOD systems. We introduce a novel dataset covering 10 core in-vehicle scenarios, allowing users to express needs naturally without system-specific commands. Task slots with varying importance levels are defined to prioritize critical information and minimize unnecessary dialogue turns. We further propose a “chain-of-validator prompting” framework that validates and refines system responses in real time, reducing misunderstandings and improving efficiency. Experimental results demonstrate that our method surpasses conventional prompting in task completion, while subjective evaluations show superior appropriateness, usability, efficiency, naturalness, and reduced cognitive load. © 2025 Copyright held by the owner/author(s).

关键词： Dialogue efficiency Human-centered conversation In-vehicle task-oriented dialogue Natural interaction

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Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories

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Synthetic and systems Biotechnology 2023年第3期8卷 498-508页

作者： Yalun Wu Qianqian Yuan Yongfu Yang Defei Liu Shihui Yang Hongwu Ma State Key Laboratory of Biocatalysis and Enzyme Engineering School of Life SciencesHubei UniversityWuhan430062HubeiChina Biodesign Center Key Laboratory of Systems Microbial BiotechnologyTianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjin300308China Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhan430062HubeiChina Artificial Intelligence and Knowledge Engineering Lab School of Computer Science and Information EngineeringHubei UniversityWuhan430062HubeiChina

High-quality genome-scale metabolic models(GEMs)could play critical roles on rational design of microbial cell factories in the classical Design-Build-Test-Learn cycle of synthetic biology *** of the constant establishment and update of GEMs for model microorganisms such as Escherichia coli and Saccharomyces cerevisiae,high-quality GEMs for non-model industrial microorganisms are still *** mobilis *** ZM4 is a non-model ethanologenic microorganism with many excellent industrial characteristics that has been developing as microbial cell factories for biochemical *** five GEMs of *** have been constructed,these models are either generating ATP incorrectly,or lacking information of plasmid genes,or not providing standard format *** this study,a high-quality GEM iZM516 of *** ZM4 was *** information from the improved genome annotation,literature,datasets of Biolog Phenotype Microarray studies,and recently updated Gene-Protein-Reaction information was combined for the curation of ***,516 genes,1389 reactions,1437 metabolites,and 3 cell compartments are included in iZM516,which also had the highest MEMOTE score of 91%among all published GEMs of *** growth was then predicted by iZM516,which had 79.4%agreement with the experimental results of the substrate *** addition,the potential endogenous succinate synthesis pathway of *** ZM4 was proposed through simulation and analysis using ***,metabolic engineering strategies to produce succinate and 1,4-butanediol(1,4-BDO)were designed and then simulated under anaerobic condition using *** results indicated that 1.68 mol/mol succinate and 1.07 mol/mol 1,4-BDO can be achieved through combinational metabolic engineering strategies,which was comparable to that of the model species *** study thus not only established a high-quality GEM iZM516 to help understand and design microbial cell fac

关键词： Genome-scale metabolic models(GEMSs) Non-model industrial microorganism Zymomonas mobilis Biolog phenotype microarray Succinate 1,4-Butanediol

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Integrated Preparation of Photonic Spin-Orbit Qudits

Integrated Preparation of Photonic Spin-Orbit Qudits

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Zhao, Haoqi Zhang, Yichi Gao, Zihe Yim, Jieun Wu, Shuang Litchinitser, Natalia M. Ge, Li Feng, Liang Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Materials Science and Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Electrical and Computer Engineering Department of Physics Duke University DurhamNC27708 United States Department of Engineering Science and Physics College of Staten Island CUNY Staten IslandNY10314 United States The Graduate Center CUNY New YorkNY10016 United States

ISBN: (纸本)9781957171395

Preparing and manipulating N-dimensional flying qudits as well as subsequently establishing their entanglement are still challenging tasks. Here, using an integrated approach, we explore the synergy from two degrees of freedom of light, spatial mode and polarization, to generate, encode, and manipulate flying photon qudits in a four-dimensional Hilbert space with high quantum fidelity, intrinsically enabling enhanced noise resilience and higher quantum data rates. © Optica Publishing Group 2024

关键词： Degrees of freedom (mechanics)

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A Way to Protect the Surveillance Data Stored in the Cloud Using FC and SVM Methods 4

A Way to Protect the Surveillance Data Stored in the Cloud U...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Suganthi, D. Raju, M. Mahesh Kumar, N.B. Vasavi, M. Washeel, Oday Faris Abdtawfeeq, Tareq Hafdhi Saveetha College of Liberal Arts and Sciences Simats Department of Computer Science Chennai Tamilnadu Thandalam602105 India Sri Krishna Arts and Science College Department of Software Systems Coimbatore India Tamil Nadu Coimbatore641 032 India Cvr College of Engineering Et Department Hyderabad India National University of Science and Technology Collage of Nursing Dhi Qar64001 Iraq

ISBN: (纸本)9798350360165

Building trust between consumers and service providers is critical to the functioning of cloud computing, a technology that offers a range of services over the Internet. When consumers choose which cloud services to utilise for processing and storing sensitive data, trust values are a major factor. In addition, service providers can employ trust values as a means of granting access to resources, protecting against malevolent users. The subjective trust model category, which evaluates trust based on user and service provider behaviour, is the one that this research suggests for trust models. Because trust is intrinsically ambiguous in our method, trust levels for cloud consumers and service providers are calculated using fuzzy logic and support vector machines. Using triangle membership functions for defuzzification and Gauss membership functions for fuzzification, we use the Mamdani fuzzy approach. In order to determine how trustworthy a resource is, our paradigm for evaluating trust takes performance and flexibility into account. Performance evaluation includes measurements related to workload and reaction time, whereas elasticity evaluation takes into account elements like scalability, availability, security, and usability. We apply fuzzy C-means clustering on pertinent criteria to establish trust levels for users, including faulty requests, fake requests, unauthorised requests, and total requests. © 2024 IEEE.

关键词： Cloud platforms

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An Efficient Deep Learning Approach to Detect Neurodegenerative Diseases Using Retinal Images

An Efficient Deep Learning Approach to Detect Neurodegenerat...

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computer science and Data engineering (CSDE), IEEE Asia-Pacific Conference on

作者： Chowdhury Mohammad Irfanuddin Wasique Islam Shafin Koushik Ahmed Md. Hasib Khan Md. Ashraful Alam Rafeed Rahman Shakib Mahmud Dipto Department of Computer Science and Engineering Brac University Dhaka Bangladesh Dept. of CSE Computer Vision and Intelligent Systems (CVIS) Research Lab Brac University Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh (ULAB) Dhaka Bangladesh

Neurodegenerative disorders like Multiple Sclerosis, Parkinson's disease, and Alzheimer's disease typically get diagnosed through brain MRI, CT scans, genetic testing, and various laboratory screening tests that are often tedious, time-consuming, and beyond the reach of the financial capability of many people especially, those living in the developing world. Moreover, they often pose potential hazards for patients with certain pre-existing conditions. To remedy this, we propose an efficient deep-learning approach that enables the detection of such neurodegenerative diseases through retinal images rather than brain images. Our proposed system can proactively detect such disorders simply through retinal scans, which are fast and cost-effective compared to traditional diagnostic approaches, which require expensive and sophisticated equipment. We used a dataset containing retinal cross-sectional images of 21 Multiple Sclerosis patients and 14 healthy individuals for our research, and our model achieved 98.85% accuracy while classifying healthy and diseased individuals from retinal scans.

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Exploring Cognitive Fatigue: Machine Learning, Forecasting, Generalization, Personalization, Inference and Labels 67th

Exploring Cognitive Fatigue: Machine Learning, Forecasting, ...

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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Nartey, David Karthikeyan, Rohith Chaspari, Theodora Mehta, Ranjana Department of Industrial and Systems Engineering Texas A&M University College StationTX United States Department of Mechanical Engineering Texas A&M University College StationTX United States Department of Computer Science and Engineering Texas A&M University College StationTX United States

Fatigue is a feeling of tiredness or weakness that can be physical, mental or both. Interpretable machine learning methods can be used for inference while having the dimension of time series prediction for developing intelligent health systems to manage fatigue. The study explored forecasting perception and performance scores associated with fatigue manifestation using cardiac activity with generalized and personalized models at a forecast interval of 10-minutes during a cognitively fatiguing task. Participants underwent a 2-hour cognitively fatiguing working memory task with subjective fatigue responses obtained every 10-minutes. Participants’ performance was calculated over the 10-minute interval. Performance labeled models had the lowest mean absolute error for forecasting in both generalized and personalized models using Gradient Boosting Regression. This provides the ability to forecast performance decrease due to fatigue and to generate fatigue mitigation interventions to reduce fatigue-related injuries. © 2023 Human Factors and Ergonomics Society.

关键词： cardiac activity Cognitive fatigue Fatigue perception heart rate Machine Learning Performance Time-series prediction

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Multiple Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV

Multiple Redundant Weighted Clustered Scheme with Dynamic We...

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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Grace Khayat Constandinos X Mavromoustakis Jordi Mongay Batalla Andreas Pitsillides Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Warsaw University of Technology Warsaw Poland Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg (Visiting Professor)

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the routing algorithms that S-UAVs utilize the most frequently is clustering, where UAVs are divided into clusters. Each cluster consists of a cluster head (CH) and cluster members (CM). The selection of the CH is a topic of continuous research because of its crucial significance in inter-cluster communication. We propose a clustered weighted method with dynamic weight modification and redundancy to ensure end-to-end communication despite non-functional CH. Interspace, speed, and performance indicators are combined into a weighted metric that is used to select the CH, redundant CHs, and CMs. The suggested technique optimizes UAV role selection by dynamically and autonomously adjusting the weights. Based on the results of the executed simulation, this is a promising strategy that minimizes data loss in an emergency situation and minimizes delay.

关键词： Measurement Conferences Computational modeling Redundancy Clustering algorithms Autonomous aerial vehicles Routing Routing protocols Delays Vehicle dynamics

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AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs 37

AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Ve...

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37th Conference on Neural Information Processing systems, NeurIPS 2023

作者： Cobb, Adam D. Roy, Anirban Elenius, Daniel Heim, F. Michael Swenson, Brian Whittington, Sydney Walker, James D. Bapty, Theodore Hite, Joseph Ramani, Karthik McComb, Christopher Jha, Susmit Computer Science Laboratory SRI International United States Mechanical Engineering Division Southwest Research Institute United States Intelligent Systems Division Southwest Research Institute United States Institute of Software Integrated Systems Vanderbilt University United States School of Mechanical Engineering Purdue University United States Department of Mechanical Engineering Carnegie Mellon University United States

ISBN: (纸本)9781713899921

We present AircraftVerse, a publicly available aerial vehicle design dataset. Aircraft design encompasses different physics domains and, hence, multiple modalities of representation. The evaluation of these cyber-physical system (CPS) designs requires the use of scientific analytical and simulation models ranging from computer-aided design tools for structural and manufacturing analysis, computational fluid dynamics tools for drag and lift computation, battery models for energy estimation, and simulation models for flight control and dynamics. AircraftVerse contains 27, 714 diverse air vehicle designs - the largest corpus of engineering designs with this level of complexity. Each design comprises the following artifacts: a symbolic design tree describing topology, propulsion subsystem, battery subsystem, and other design details;a STandard for the Exchange of Product (STEP) model data;a 3D CAD design using a stereolithography (STL) file format;a 3D point cloud for the shape of the design;and evaluation results from high fidelity state-of-the-art physics models that characterize performance metrics such as maximum flight distance and hover-time. We also present baseline surrogate models that use different modalities of design representation to predict design performance metrics, which we provide as part of our dataset release. Finally, we discuss the potential impact of this dataset on the use of learning in aircraft design and, more generally, in CPS. AircraftVerse is accompanied by a data card, and it is released under Creative Commons Attribution-ShareAlike (CC BY-SA) license. The dataset is hosted at https://***/record/6525446, baseline models and code at https://***/SRI-CSL/AircraftVerse, and the dataset description at https://***/. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： computer aided logic design

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Progress in research on ultrasound radiomics for predicting the prognosis of breast cancer

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Cancer Innovation 2023年第4期2卷 283-289页

作者： Xuantong Gong Xuefeng Liu Xiaozheng Xie Yong Wang Department of Ultrasound National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBejjing Advanced Innovation Center for Big Data and Brain Computing(BDBC)Beihang UniversityBeijingChina School of Computer and Communication Engi neering.University of Science and Technology Beijing BeijingChina

Breast cancer is the most common malignant tumor and the leading cause of cancer-related deaths in women *** means of predicting the prognosis of breast cancer are very helpful in guiding treatment and improving patients'*** extracted by radiomics reflect the genetic and molecular characteristics of a tumor and are related to its biological behavior and the patient's ***,radiomics provides a new approach to noninvasive assessment of breast cancer *** is one of the commonest clinical means of examining breast *** recent years,some results of research into ultrasound radiomics for diagnosing breast cancer,predicting lymph node status,treatment response,recurrence and survival times,and other aspects,have been *** this article,we review the current research status and technical challenges of ultrasound radiomics for predicting breast cancer *** aim to provide a reference for radiomics researchers,promote the development of ultrasound radiomics,and advance its clinical application.

关键词： breast cancer deeplearning prognosisprediction radiomics ultrasound

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