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The Study of the intelligent Voice Man-machine Interaction on the Display Console 3

The Study of the Intelligent Voice Man-machine Interaction o...

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3rd international Conference on computer Vision and pattern analysis, ICCPA 2023

作者： Lv, Wenfa Shi, Hui Zhong, Xu Feng, Zhiwen China Shipbuilding Industry Group Jiangsu Automation Research Institute Lianyungang222006 China

ISBN: (纸本)9781510667563

In the fact of shortcomings in traditional man-machine interaction, the display console based on the intelligent voice non-contact man-machine interaction is studied in this paper, which avoids problems in incorrect manipulation and difficult operation to a extent. With the development of intelligent voice technology, speech recognition, speech synthesis and speech enhancement are widely used instead of traditional mouse, keyboard and numeric keypad. Several typical applications are introduced in the study, which can be a reference for other display consoles. © 2023 SPIE.

关键词： Speech recognition

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computer Linguistic Systems Design and Development Features for Ukrainian Language Content Processing 8

Computer Linguistic Systems Design and Development Features ...

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8th international Conference on Computational Linguistics and intelligent Systems. Volume III: intelligent Systems workshop, ISW-CoLInS 2024

作者： Vysotska, Victoria Lviv Polytechnic National University Stepan Bandera Street 12 Lviv79013 Ukraine

The paper describes the developed IT (information technology) processing of Ukrainian-language text content, unlike the existing ones, which supports the modularity principle of the typical CLS (computer linguistic system) architecture for solving a specific NLP (natural language processing) problem and analysing a set of parameters and metrics of the system's functioning by the target audience behaviour. The general structure of CLS for the processing of text content in the Ukrainian language and the conceptual scheme/model of the functioning of a typical CLS based on the modelling of the interaction of the main processes and components of the system were developed, which made it possible to improve IT intellectual analysis of the text flow based on the processing of information resources. The peculiarities of the design and development of computer linguistic systems are analysed based on the definition of the main stages such as grapheme, morphological, lexical, and syntactic-semantic analysis/synthesis of the Ukrainian-language text for a specific NLP problem solution. The formulation of the problem of processing the Ukrainian-language text based on the definition of the functional features of the intellectual analysis of the text flow was made and specified. The general analysis of the problem of analysis of the Ukrainian-language text and the definition of the main problems of the processing of the Ukrainian-language text made it possible to formulate the main stages and requirements for the project of a typical CLS solution of a specific NLP problem. Identification of the main characteristics of CLS and justification of the project implementation of a typical CLS made it possible to determine the expected effects of the corresponding project implementation. Based on the analysis of the input/output streams of the content of the computer linguistic system, the functional requirements for the project of a typical CLS, its software modules, network, software and

关键词： Machine learning

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Advancements in Weather Forecasting: A Review of Satellite Imagery and AI Integration 9

Advancements in Weather Forecasting: A Review of Satellite I...

引用

9th international Conference on intelligent Informatics and BioMedical Sciences, ICIIBMS 2024

作者： Liu, Yunxiang Cai, Shixuan Shanghai Institute of Technology School of Computer Information Engineering China

ISBN: (纸本)9798350363043

This review examines the integration of meteorological satellite imagery with artificial intelligence (AI), focusing on traditional machine learning and deep learning methods in weather forecasting. It begins by explaining the basic concepts and importance of satellite imagery in capturing highresolution atmospheric data. The study highlights how AI, especially deep learning, improves the analysis of these complex datasets, enhancing weather pattern identification and anomaly detection. We discuss the integration of satellite data with traditional forecasting methods, recent advancements in hybrid algorithms, and sophisticated data assimilation techniques. The review also covers deep learning models like CNNs, RNNs, and GANs, demonstrating their superior performance in predicting weather phenomena. Challenges such as high computational costs, resource requirements, and model generalizability are addressed, along with future directions in model optimization and hybrid approaches. This synthesis underscores the significant impact of combining satellite imagery with AI on weather forecasting accuracy and reliability. © 2024 IEEE.

关键词： Weather satellites

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Hyperspectral Image Reconstruction in Remote Sensing: LaplaceGAN synthesis Coupled with VGG-UNet Classification

Hyperspectral Image Reconstruction in Remote Sensing: Laplac...

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2024 international Symposium on Computing and intelligent Systems, SCI 2024

作者： Sain, Shikha Saxena, Monika Department of Computer Science Banasthali Vidyapith Rajasthan Jaipur304022 India

Enhancing and reconstructing environmental images involve refining visual data to improve quality and reconstructing scenes. In remote sensing, this aids in accurate analysis, contributing to advanced understanding and decision-making. This study focuses on advancing hyperspectral image analysis in remote sensing through the design of a deep learning-based model aimed at enhancing and reconstructing environmental images. An integral aspect involves introducing a novel approach using LaplaceGAN to generate synthetic images with high fidelity, building upon real images as a foundational basis. Furthermore, the study proposes the implementation of a specialized VGG-UNet architecture tailored for the classification of hyperspectral images, specifically addressing the nuances of remote sensing data. To assess the model's efficacy, a comparative analysis is conducted, pitting the performance of VGG-UNet against alternative methods such as Res-UNet and Faster R-CNN in the context of remote sensing image classification. This research aims to contribute to the field by designing a deep learning model that not only analyzes hyperspectral images comprehensively but also enhances and reconstructs environmental images, thereby advancing the most recent methods for better comprehension and judgement in a range of remote sensing applications. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Remote sensing

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Alexa, What's Inside of You? A Qualitative Study to Explore Users' Mental Models of intelligent Voice Assistants 23

Alexa, What's Inside of You? A Qualitative Study to Explore ...

引用

23rd ACM international Conference on intelligent Virtual Agents (IVA)

作者： Horstmann, Aike C. Strathmann, Clara Lambrich, Lea Kraemer, Nicole C. Univ Duisburg Essen Social Psychol Media & Commun Duisburg Germany

ISBN: (纸本)9781450399944

Despite the rising prevalence of intelligent voice assistants in people's homes, it remains opaque to most users how they function. With the overall goal to foster informed usage and responsible handling of personal data, the user's understanding increasingly moves into the focus of research. Particularly in the context of black box technologies such as voice assistants, individuals build intuitive mental models (also called folk theories) which can act as a guide for how they understand and interact with such systems. To shed light on individuals' mental models regarding intelligent voice assistants, we applied a visual elicitation method during a citizen science workshop: 26 participants were asked to visualize how they imagine a voice assistant to function. The resulting drawings were categorized based on their theorization complexity level. While basic awareness of the overall functionality (user input - something happens - voice assistant output) was found in every drawing, 13 participants revealed mental models on how the input is received (e.g., audio recording and speech processing), six on how the information is then processed (e.g., database requests and data categorization), and five on how the output is generated (e.g., speech synthesis). Overall, the results underline the need to address individuals' gaps in understanding of intelligent technology that is already in widespread use.

关键词： Human-computer Interaction Voice Assistants Mental Models Visualization Qualitative analysis

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19th workshop on Dependable Smart Embedded and Cyber-Physical Systems and Systems-of-Systems, DECSoS 2024, 11th international workshop on Next Generation of System Assurance Approaches for Critical Systems, SASSUR 2024, Towards A Safer Systems architecture Through Security, TOASTS 2024 and 7th international workshop on Artificial Intelligence Safety Engineering, WAISE 2024 held in conjunction with the 43rd international Conference on computer Safety, Reliability, and Security, SAFECOMP 2024

19th Workshop on Dependable Smart Embedded and Cyber-Physica...

引用

19th workshop on Dependable Smart Embedded and Cyber-Physical Systems and Systems-of-Systems, DECSoS 2024, 11th international workshop on Next Generation of System Assurance Approaches for Critical Systems, SASSUR 2024, Towards A Safer Systems architecture Through Security, TOASTS 2024 and 7th international workshop on Artificial Intelligence Safety Engineering, WAISE 2024 held in conjunction with the 43rd international Conference on computer Safety, Reliability, and Security, SAFECOMP 2024

ISBN: (纸本)9783031687372

The proceedings contain 36 papers. The special focus in this conference is on computer Safety, Reliability, and Security. The topics include: Security and Safety in Urban Environments: Evaluating Threats and Risks of Autonomous Last-Mile Delivery Robots;safe Road-Crossing by Autonomous Wheelchairs: A Novel Dataset and Its Evaluation;automating an Integrated Model-Driven Approach to Analysing the Impact of Cyberattacks on Safety;Securing Web Access: PUF-Driven Two-Factor Authentication for Enhanced Protection;enhancing Tunnel Safety with Artery V2X Simulation for Real-Time Risk Assessment;detecting and Mitigating Errors in Neural Networks;challenges and Limitations of Utilizing Multi-core/Heterogeneous Logic Elements in the Railway Signaling Applications;identifying Difficult Environmental Conditions with Scenario-Based Hazard and Fault analysis;Using GPT-4 to Generate Failure Logic;towards an Argument pattern for the Use of Safety Performance Indicators;enabling Theory-Based Continuous Assurance: A Coherent Approach with Semantics and Automated synthesis;Managing Changing Product Liability Obligations Emerging from New Proposed EU Directive;reaching Consensus on System-of-Systems Resilience Assurance: A Case of Mobility as a Service;a Deductive Approach to Safety Assurance: Formalising Safety Contracts with Subjective Logic;a New Approach to Creating Clear Operational Safety Arguments;including Defeaters in Quantitative Confidence Assessments for Assurance Cases;multivariate Security Breach Probability: The Gordon-Loeb Model with Copulas;quantum Machine Learning: Perspectives in Cybersecurity;Security Modeling Challenges and Research Directions Around the ADVISE Meta Framework;Capability Ambient DO – A Usable Tool for Linux System Security;VUOS: A User-Space Hypervisor Based on System Call Hijacking;cyber Risk Propagation on Networks;where Do Safety and Security Mutually Reinforce? A Multi-level Model-Based Approach for a Consistent Interplay;a Flow-Based Credibilit

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Conceptualizing Agency: A Framework for Human-AI Interaction

Conceptualizing Agency: A Framework for Human-AI Interaction

引用

Joint of the ACM workshops at the international Conference on intelligent User Interfaces 2025, IUI-WS 2025

作者： Zhang, Alexander Varshney, Lav R. University of Illinois Urbana-Champaign Department of Philosophy United States University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering United States

This paper proposes a framework for understanding intentional agency in the context of increasingly autonomous AI systems. As AI tools perform complex tasks independently, they challenge our traditional notions of agency-particularly the ability to act intentionally, grounded in what Anscombe calls "practical knowledge." We explore intentional agency through three lenses: (1) Anscombe's concept of intention, where we examine how AI tools complicate human intentionality and our ability to give reasons for actions;(2) shared intention, which frames agency in joint human activities;and (3) relational intention, a novel synthesis drawing on Anscombe and Fiske's Relational Models Theory which captures how relationships shift between different relational models. Our analysis reveals that agency is not merely an individual capacity but is fundamentally shaped by relationships with others who can interpret and respond to our reasons. AI systems, however, disrupt this dynamic: while they assist in tasks, they lack the intersubjectivity required to engage in mutual reason-giving, potentially diminishing our practical knowledge and intentional agency. We conclude that AI should be designed to support human-human relationships rather than supplant them, with humans retaining relational authority in human-AI interactions to preserve agency. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Agency Anscombe Generative AI Human-AI co-creation Relational Models Theory

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Array pattern synthesis with Discrete Phases for Reconfigurable intelligent Surfaces

Array Pattern Synthesis with Discrete Phases for Reconfigura...

引用

IEEE workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Xiao Cai Hei Victor Cheng Department of Electrical and Computer Engineering Aarhus University Denmark

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

Extensive research on Reconfigurable intelligent Surfaces (RIS) has primarily revolved around optimizing phase coefficients for passive beamforming in specific target directions. This optimization typically presumes prior knowledge of the target direction, a premise that is not valid during initial sensing phases where the target’s location is unknown. To enhance direction estimation, a broader beam is required, presenting the array pattern synthesis problem: the need to maximize received power over an entire target area. While this challenge has been addressed with active antennas, RIS systems pose a unique problem due to their inherent continuous or discrete phase constraints. Our study introduces a novel array pattern synthesis method tailored for discrete phase constraints in RIS. We introduce a penalty method that pushes these constraints to the boundary of the convex hull. Then the Minorization-Maximization (MM) method is utilized to reformulate the problem into a convex one. Our numerical results illustrate that our algorithm is capable of generating a wide beam pattern comparable to scenarios with per-power constraints where both the amplitudes and phases are adjustable, evidencing its proficiency in creating wide beams crucial for wireless communication and sensing in the absence of prior knowledge of the target’s location.

关键词： Phased arrays Wireless communication Conferences Signal processing algorithms Estimation Reconfigurable intelligent surfaces Minimax techniques Sensors Optimization Surface treatment

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pattern synthesis of Sparse Linear Arrays with Mutual Coupling Using Vectorial Matrix Pencil Method

Pattern Synthesis of Sparse Linear Arrays with Mutual Coupli...

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international workshop on Antenna Technology: Small Antennas and Novel Metamaterials, iWAT

作者： Yuanchen Zeng Koen Mouthaan Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798331527365

ISBN: (纸本)9798331527372

A challenging research question is how to achieve a desired pattern of an antenna array with the least number of antenna elements while including mutual coupling. The matrix pencil method (MPM) simplifies the derivation by assuming that the elements are isotropic and that there is no mutual coupling. However, in practical engineering, the desired pattern is scalar while the element patterns are vectorial and different due to the presence of mutual coupling, rendering traditional MPM less applicable. Here, a vectorial MPM (VMPM) is presented that takes mutual coupling effects into account. First, a Hankel sampling matrix is constructed from the desired radiation pattern, and singular value decomposition (SVD) is performed to obtain the minimum number of elements. Next, the sampling matrix is used to construct the matrix pencil to determine the positions of the elements. Furthermore, intelligent optimization algorithms are introduced to obtain the element excitations considering mutual coupling effects. Finally, the effectiveness of the proposed method is validated by a numerical case.

关键词： Mutual coupling Conferences Rendering (computer graphics) Sparse matrices Matrix decomposition Optimization Antenna arrays Singular value decomposition Antenna radiation patterns

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Novel Fault Diagnosis Method Integrating D-L2-FDA and AdaBoost 8th

Novel Fault Diagnosis Method Integrating D-L2-FDA and AdaBo...

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8th international workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2023

作者： Zhao, Yang Ke, Wei Zhang, Wei Luo, Yi Zhu, Qun-Xiong He, Yan-Lin Zhang, Yang Zhang, Ming-Qing Xu, Yuan College of Information Science and Technology Beijing University of Chemical Technology Beijing100029 China Engineering Research Center of Intelligent PSE Ministry of Education of China Beijing100029 China School of Applied Sciences Macao Polytechnic Institute SAR 999078 China Research Institute of Mine Big Data Chinese Institute of Coal Science Beijing100013 China

ISBN: (纸本)9789819975891

Industrial process safety has always been a concern for engineers and researchers. Fault diagnosis frameworks based on data-driven methods are prevalent and play a vital role in guaranteeing industrial process safety. However, the data collected in actual industrial production regularly exhibits high-dimensional and complex timing characteristics. In this research, a new framework for fault diagnosis is constructed on the strength of dynamic L2-norm normalized fisher discriminant analysis (FDA) integrating with AdaBoost. Firstly, timing characteristic in industrial process is taken into account so that a dynamic fault dataset is constructed. Then, the FDA vectors are normalized by L2-norm and utilized to reduce data dimension which can learn fault patterns in feature extraction. In addition, an ensemble learning method named AdaBoost is adopted for pattern classification. To verify the effectiveness of the proposed method, simulation experiments based on Tennessee Eastman process are carried out and satisfactory results are obtained. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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