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IEEE Southeastcon

作者： Ziyu Chen Selam B. Kelil Mohammad Y. M. Naser Jason S. Metcalfe Sylvia Bhattacharya Electrical & Computer Engineering Department Kennesaw State University Marietta USA Computer Science Department Kennesaw State University Marietta USA US DEVCOM Army Research Laboratory Aberdeen Proving Ground Aberdeen USA Engineering Technology Department Kennesaw State University Marietta USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Artificial Intelligence (AI) systems frequently exhibit systematic blind spots, often referred to as hallucinations in Large Language Models (LLMs), posing risks in high-stakes applications such as autonomous systems, security, and military operations. This paper explores how human intuitive responses, along with conscious reasoning processes, can be integrated to mitigate AI blind spots and enhance decision-making effectiveness within Human-AI teams. We introduce Human-Guided Artificial Intelligence (HGAI) as a framework for achieving this goal. Specifically, we examine the role of System-1 intuitive processing, as captured through physiological signals such as electroencephalography (EEG) and electrocardiography (ECG), System-2 reasoning-based decision-making, and Multi-Modal Fusion (MMF) mechanisms while assessing the knowledge required to develop more reliable, context-aware, and ethically aligned intelligent decision-making systems for highly complex environments.

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Identifying key features from app user reviews 21

Identifying key features from app user reviews

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43rd IEEE/ACM International Conference on Software Engineering, ICSE 2021

作者： Wu, Huayao Deng, Wenjun Niu, Xintao Nie, Changhai State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University China

ISBN: (纸本)9780738113197

Due to the rapid growth and strong competition of mobile application (app) market, app developers should not only offer users with attractive new features, but also carefully maintain and improve existing features based on users' feedbacks. User reviews indicate a rich source of information to plan such feature maintenance activities, and it could be of great benefit for developers to evaluate and magnify the contribution of specific features to the overall success of their apps. In this study, we refer to the features that are highly correlated to app ratings as key features, and we present KEFE, a novel approach that leverages app description and user reviews to identify key features of a given app. The application of KEFE especially relies on natural language processing, deep machine learning classifier, and regression analysis technique, which involves three main steps: 1) extracting feature-describing phrases from app description;2) matching each app feature with its relevant user reviews;and 3) building a regression model to identify features that have significant relationships with app ratings. To train and evaluate KEFE, we collect 200 app descriptions and 1,108,148 user reviews from Chinese Apple App Store. Experimental results demonstrate the effectiveness of KEFE in feature extraction, where an average F-measure of 78.13% is achieved. The key features identified are also likely to provide hints for successful app releases, as for the releases that receive higher app ratings, 70% of features improvements are related to key features. © 2021 IEEE.

关键词： Feature extraction

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Reasoning about Strategic Abilities in Stochastic Multi-agent Systems

arXiv

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arXiv 2024年

作者： Zhang, Yedi Song, Fu Chen, Taolue Wu, Xuzhi Department of Computing Science National University of Singapore Singapore State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China School of Computing and Mathematical Sciences Birkbeck University of London United Kingdom College of Computer Science and Software Engineering Shenzhen University China

Reasoning about strategic abilities is key to AI systems comprising multiple agents, which provide a unified framework for formalizing various problems in game theory, social choice theory, etc. In this work, we propose a probabilistic extension of the alternating-time μ-calculus (AMC), named PAMC, for reasoning about the strategic abilities of agents in stochastic multi-agent systems. We show that PAMC subsumes two existing logics AMC and PμTL (a probabilistic extension of the modal μ-calculus), but is incomparable with the probabilistic alternating-time temporal logic (PATL). We study the problems of model checking and satisfiability checking for PAMC. We first give a model checking algorithm by leveraging algorithms for solving normal-form games and AMC model checking. We establish that the model checking problem of PAMC remains in UP∩co-UP, the same complexity class as the model checking problem for AMC and PμTL. We also provide a new reduction from the satisfiability problem of PAMC to solving parity games, by which we obtain an EXPTIME decision procedure, as well as the small model property which allows to construct a model for each satisfiable PAMC formula. Satisfiability in PAMC has the same complexity as in the modal μ-calculus, unlike PCTL and PATL whose satisfiability checking problems remain open. We have implemented both the model checking and satisfiability checking algorithms as open-source tools. Experimental results are reported, showcasing the practical applications and effectiveness of our approaches. © 2024, CC BY.

关键词： Stochastic systems

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FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices

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Fire Ecology 2023年第1期19卷 1-19页

作者： Ahmad, Khubab Khan, Muhammad Shahbaz Ahmed, Fawad Driss, Maha Boulila, Wadii Alazeb, Abdulwahab Alsulami, Mohammad Alshehri, Mohammed S. Ghadi, Yazeed Yasin Ahmad, Jawad Faculty of Engineering and Technology Multimedia University Melaka Malaysia School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK Department of Cyber Security Pakistan Navy Engineering College NUST Karachi Pakistan Robotics and Internet of Things Laboratory Prince Sultan University Riyadh Saudi Arabia RIADI Laboratory National School of Computer Sciences University of Manouba Manouba Tunisia Department of Computer Science College of Computer Science and Information Systems Najran University Najran Saudi Arabia Department of Software Engineering Computer Science Al Ain University Abu Dhabi United Arab Emirates

Forests cover nearly one-third of the Earth’s land and are some of our most biodiverse ecosystems. Due to climate change, these essential habitats are endangered by increasing wildfires. Wildfires are not just a risk to the environment, but they also pose public health risks. Given these issues, there is an indispensable need for efficient and early detection methods. Conventional detection approaches fall short due to spatial limitations and manual feature engineering, which calls for the exploration and development of data-driven deep learning solutions. This paper, in this regard, proposes 'FireXnet', a tailored deep learning model designed for improved efficiency and accuracy in wildfire detection. FireXnet is tailored to have a lightweight architecture that exhibits high accuracy with significantly less training and testing time. It contains considerably reduced trainable and non-trainable parameters, which makes it suitable for resource-constrained devices. To make the FireXnet model visually explainable and trustable, a powerful explainable artificial intelligence (AI) tool, SHAP (SHapley Additive exPlanations) has been incorporated. It interprets FireXnet’s decisions by computing the contribution of each feature to the prediction. Furthermore, the performance of FireXnet is compared against five pre-trained models — VGG16, InceptionResNetV2, InceptionV3, DenseNet201, and MobileNetV2 — to benchmark its efficiency. For a fair comparison, transfer learning and fine-tuning have been applied to the aforementioned models to retrain the models on our dataset. The test accuracy of the proposed FireXnet model is 98.42%, which is greater than all other models used for comparison. Furthermore, results of reliability parameters confirm the model’s reliability, i.e., a confidence interval of [0.97, 1.00] validates the certainty of the proposed model’s estimates and a Cohen’s kappa coefficient of 0.98 proves that decisions of FireXnet are in considerable accordance with t

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Target-Oriented WiFi Sensing for Respiratory Healthcare: from Indiscriminate Perception to In-Area Sensing

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IEEE Network 2024年

作者： Wang, Meng Huang, Jinyang Zhang, Xiang Liu, Zhi Li, Meng Zhao, Peng Yan, Huan Sun, Xiao Dong, Mianxiong Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligence Machine School of Computer and Information Hefei230601 China University of Science and Technology of China CAS Key Laboratory of Electromagnetic Space Information Hefei230026 China The University of Electro-Communications Department of Computer and Network Engineering Tokyo1828585 Japan Guizhou Normal University School of Big Data and Computer Science Guiyang550025 China Muroran Institute of Technology Department of Sciences and Informatics 0508585 Japan

Driven by the vision of integrated sensing and communication (ISAC) toward 6G technology, the WiFi-based respiration sensing approach has emerged as a highly competitive candidate for advanced healthcare services. Nevertheless, the indiscriminate perception of all the moving objects within the sensing area raises challenges for system stability and robustness for real-world deployment, especially for the susceptibility to motion interference from other people. Meanwhile, thanks to the emerging in-area wireless sensing technologies, i.e., beamforming, the dynamic environment tolerance of these technologies gives crucial opportunities for target-oriented WiFi-based healthcare services. This article discusses the compelling intersection of in-area WiFi sensing and the future of target-oriented intelligent respiratory healthcare network services. We first present a novel WiFi-based healthcare-assisting framework tailored for inter-user motion interference-tolerable (IMIT) sensing. The detailed components of low-level signal preprocessing, target-direction signal extraction, and healthcare-related services are discussed. By utilizing CSI beamforming technology, which adjusts a directional beam toward the desired direction and adaptively places beam nulls in noisy directions, we can mitigate motion interference and achieve target-oriented healthcare sensing. Finally, we discuss open challenges and potential solutions for target-oriented WiFi healthcare sensing. © 1986-2012 IEEE.

关键词： Wireless local area networks (WLAN)

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Optimisation of alloy composition for highly-formable magnesium sheet

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International Journal of Minerals,Metallurgy and Materials 2022年第7期29卷 1388-1395页

作者： Zhuoran Zeng Mingzhe Bian Shiwei Xu Weineng Tang Chris Davies Nick Birbilis Jianfeng Nie College of Engineering and Computer Science Australian National UniversityACT.2601Australia Department of Materials Science and Engineering Monash UniversityVIC 3800Australia State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan UniversityChangsha 410082China Research Institute(R&D Center) Baosteel Group CorporationShanghai 201999China Department of Mechanical and Aerospace Engineering Monash UniversityVIC 3800Australia

The effectiveness of Ca or Gd addition on ductility and formability of Mg-Zn-Zr based dilute alloys in deep drawing has not been systematically compared *** this study,formable Mg-Zn-Gd-Zr and Mg-Zn-Ca-Zr sheet alloys are produced by hot *** sheets have similarly weakened basal texture,but the sheet of the Mg-Zn-Gd-Zr alloys has higher ductility and formability than that of Mg-Zn-Ca-Zr *** combined addition of 0.2wt%Ca and 0.4wt%Gd to the Mg-1Zn-0.5Zr(wt%)alloy leads to a Mg-1Zn-0.4Gd-0.2Ca-0.5Zr alloy that has even better ductility,and its formability during deep drawing is comparable to the benchmark Al6016 *** increase in Ca content from 0.2wt%to 0.5wt%leads to decreased sheet ductility and formability,predominantly due to grain boundary embrittlement.

关键词： magnesium sheet alloy texture microstructure formability solute segregation

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Enhancing Event Tagger with Automatic Speech Recognizer for Audio Multi-task Scenarios by Distillation with Pre-Trained Large Models

Enhancing Event Tagger with Automatic Speech Recognizer for ...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Cheng, Jianfeng Liu, Ye Yin, Jian Wang, Liangdao Pan, Yan Lizhi Inc. Artificial Intelligence Department Guangzhou Beijing China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China School of Artificial Intelligence Sun Yat-sen University Zhuhai China

ISBN: (纸本)9781665410205

With the continuous expansion of robotics and digital humans in practical applications, the demand for the auditory system is becoming deeper, usually requiring more efficient speech recognition framework capabilities to handle multiple tasks and use fewer resources. In previous audio processing frameworks, each type of audio processing task typically requires constructing a standalone deep network model for training, which results in more training data and higher training time when constructing models for multi-task audio scenarios simultaneously. The recent improvement of audio models based on transformers have brought about methods that can handle multiple audio tasks concurrently. However, recent related methods still require retraining multi-task targets with an amount of data, and achieve the general effect after training for multi-task scenarios than the simple combination of standalone methods processed separately. In order to better build a model that can handle multiple audio tasks, we propose a novel framework of distillation through pre-trained large models for enhancing event tagger with automatic speech recognizer. Through multiple rounds of experiments on several audio datasets, it has been verified that the proposed framework can achieve better results than the baseline for multitasking, and comparative results with less parameters compared to the baselines for single-task scenarios. © 2024 IEEE.

关键词： Continuous speech recognition

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Versatile Test Reactor Open Digital Engineering Ecosystem

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Insight 2025年第1期28卷 64-68页

作者： Ritter, Christopher Browning, Jeren Suyderhoud, Peter Hays, Ross Marshall, AnnMarie Han, Kevin Ashbocker, Taylor Darrington, John Nelson, Lee Idaho National Laboratory Department of Digital Systems & Engineering Versatile Test Reactor Program Idaho FallsID83401 United States Pivotal Solutions 3 Grace Avenue Suite 162 Great NeckNY11021 United States North Carolina State University Department of Civil and Environmental Engineering United States Department of Computer Science University of Illinois at Urbana-Champaign 205 N. Mathews Ave. UrbanaIL61801 United States

Modern design of nuclear facilities represents unique challenges: enabling the design of complex advanced concepts, supporting geographically dispersed teams, and supporting first-of-a-kind system development. Errors made early in design can introduce silent errors. These errors can cascade causing unknown risk of complex engineering programs. The Versatile Test Reactor (VTR) Program uses digital-engineering principles for design, procurement, construction, and operation to reduce risk and improve efficiencies. Digital engineering is an integrated, model-based approach which connects proven digital tools such as building information management (BIM), project controls, and systems-engineering software tools into a cohesive environment. The VTR team hypothesizes using these principals can lead to similar risk and cost reductions and schedule efficiencies observed in other engineering industries. This research investigates the use of a digital engineering ecosystem in the design of a 300-MWt sodium-cooled fast reactor. This ecosystem was deployed to over 200 engineers and used to deliver the conceptual design of the VTR. We conclude that initial results show significant reductions in user latency (1000x at peak use), the possibility of direct finite-element-analysis (FEA) integrations to computer-aided design (CAD) tools, and nuclear reactor system design descriptions (SDDs) that we can fully link throughout design in data-driven requirements-management software. These early results led to the VTR maintaining milestone performance during the COVID-19 pandemic. Copyright © 2022 by Idaho National laboratory. Published by INCOSE with permission.

关键词： Sodium-cooled fast reactors

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Geometric Distortion Guided Transformer for Omnidirectional Image Super-Resolution

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IEEE Transactions on Circuits and Systems for Video Technology 2025年第6期35卷 5166-5181页

作者： Yang, Cuixin Dong, Rongkang Xiao, Jun Zhang, Cong Lam, Kin-Man Zhou, Fei Qiu, Guoping The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong Shenzhen University College of Electronic and Information Engineering Shenzhen518060 China Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication Shenzhen518060 China University of Nottingham NottinghamNG8 1BB United Kingdom School of Computer Science NingboNG8 1BB China

As virtual and augmented reality applications gain popularity, omnidirectional image (ODI) super-resolution has become increasingly important. Unlike 2D plain images that are formed on a plane, ODIs are projected onto spherical surfaces. Applying established image super-resolution methods to ODIs, therefore, requires performing equirectangular projection (ERP) to map the ODIs onto a plane. ODI super-resolution needs to take into account geometric distortion resulting from ERP. However, without considering such geometric distortion of ERP images, previous methods only utilize a limited range of pixels and may easily miss self-similar textures for reconstruction. In this paper, we introduce a novel Geometric Distortion Guided Transformer for Omnidirectional image Super-Resolution (GDGT-OSR). Specifically, a distortion modulated rectangle-window selfattention mechanism, integrated with deformable self-attention, is proposed to better perceive the distortion and thus involve more self-similar textures. Distortion modulation is achieved through a newly devised distortion guidance generator that produces guidance for the rectangular windows by exploiting the variability of distortion across latitudes. Furthermore, we propose a dynamic feature aggregation scheme to adaptively fuse the features from different self-attention modules. We present extensive experimental results on public datasets and show that the new GDGT-OSR outperforms methods in existing literature. © 1991-2012 IEEE.

关键词： Image resolution

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I WANT TO PLAY PIANO Chasing a Dream with Netychords

I WANT TO PLAY PIANO Chasing a Dream with Netychords

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

作者： Moreno, Davys Caixinha, Helder Davanzo, Nicola Avanzini, Federico Research Centre on Didactics and Technology in the Education of Trainers University of Aveiro Aveiro Portugal DigiMedia DeCA University of Aveiro Aveiro Portugal Laboratory of Music Informatics University of Milan Milan Italy Department of Computer Science University of Milan Milan Italy

ISBN: (纸本)9798400713958

A child with motor and communication disabilities due to cerebral palsy learned music and piano in an artistic school in Portugal through an intervention that emphasized pedagogical differentiation and curricular adaptations, integrating technology, software, and assistive devices. This article introduces the Netychords Accessible Digital Musical Instrument (ADMI), which the child uses alongside Assistive Technologies to perform on a virtual piano with the Symphony Orchestra of the University of Aveiro. Netychords demonstrates how digital technologies can create accessible instruments, enabling musical expression for individuals with motor limitations. The adaptive design process behind Netychords, tailored to the child’s abilities, serves as a model for similar solutions in special needs contexts. By extending access to music education and artistic participation, such innovations highlight the potential of inclusive approaches to empower individuals with disabilities, fostering creativity and enabling active involvement in cultural and artistic endeavours. © 2025 Copyright held by the owner/author(s).

关键词： Electronic musical instruments

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