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Leveraging Augmented Reality,Semantic-Segmentation,and VANETs for Enhanced Driver’s Safety Assistance

computers, Materials & Continua 2024年第1期78卷 1443-1460页

作者： Sitara Afzal Imran Ullah Khan Irfan Mehmood Jong Weon Lee Mixed Reality and Interaction Lab Department of SoftwareSejong UniversitySeoul05006Korea Faculty of Engineering and Digital Technologies School of Computer ScienceAI and ElectronicsUniversity of BradfordBradfordUK

Overtaking is a crucial maneuver in road transportation that requires a clear view of the road ***,limited visibility of ahead vehicles can often make it challenging for drivers to assess the safety of overtaking maneuvers,leading to accidents and *** this paper,we consider atrous convolution,a powerful tool for explicitly adjusting the field-of-view of a filter as well as controlling the resolution of feature responses generated by Deep Convolutional Neural Networks in the context of semantic image *** article explores the potential of seeing-through vehicles as a solution to enhance overtaking ***-through vehicles leverage advanced technologies such as cameras,sensors,and displays to provide drivers with a real-time view of the vehicle ahead,including the areas hidden from their direct line of *** address the problems of safe passing and occlusion by huge vehicles,we designed a see-through vehicle system in this study,we employed a windshield display in the back car together with cameras in both *** server within the back car was used to segment the car,and the segmented portion of the car displayed the video from the front *** see-through system improves the driver’s field of vision and helps him change lanes,cross a large car that is blocking their view,and safely overtake other *** network was trained and tested on the Cityscape dataset using semantic *** transparent technique will instruct the driver on the concealed traffic situation that the front vehicle has *** our findings,we have achieved 97.1% *** article also discusses the challenges and opportunities of implementing see-through vehicles in real-world scenarios,including technical,regulatory,and user acceptance factors.

关键词： Overtaking safety augmented reality VANET V2V deep learning

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JoTyMo: Joint Type and Movement Detection from RGB Images of before and after Interacting with Articulated Objects 11

JoTyMo: Joint Type and Movement Detection from RGB Images of...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Forootan, Ehsan Ghasemi, Hamed Masouleh, Mehdi Tale Kalhor, Ahmad Moshiri, Behzad University of Tehran Human and Robot Interaction Laboratory Electrical and Computer Engineering Department Iran

ISBN: (纸本)9798350308105

This paper presents a CNN-based network architecture aimed to classify and detect joint types within Articulated objects, specifically the Push-P joints, P-joints, R-joints and objects lacking joints. The movement modeling of the detected objects is explored by processing pre and post interaction RGB images within the SAPIEN PartNet-Mobility dataset. In order to achieve this, an architecture is proposed to leverage consecutive CNN encoders based on the VGG architecture, in order to classify joints based on pre and post-interaction images. Additionally, in order to detect the effect-point and movement vector, a convolutional encoder is applied for each joint type. Moreover, extensive evaluation is made to showcase the results, achieving 96% accuracy in joint classification and 94% accuracy in regression on the considered dataset. Elaborate details regarding network architectures, training procedures, and testing methodologies are available at source code repository. © 2023 IEEE.

关键词： Network architecture

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Conversational Agents on Your Behalf: Opportunities and Challenges of Shared Autonomy in Voice Communication for Multitasking 25

Conversational Agents on Your Behalf: Opportunities and Chal...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Cheng, Yi Fei Shirado, Hirokazu Kasahara, Shunichi Sony Computer Science Laboratories Inc. Tokyo Japan Okinawa Institute of Science and Technology Graduate University Okinawa Japan Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9798400713941

Advancements in computational agents will enable them to act as surrogates for users in online communication, promising enhanced productivity by supporting multitasking. This capability may be especially powerful when combined with human control, allowing users to retain agency while achieving better performance than either human or agent alone. However, it remains unclear how people might leverage this technology to multitask effectively. We present a study with 18 dyads exploring how users employ automated responses to support an arithmetic task while staying engaged in a voice call. Participants multitasked with a conversational agent under three levels of autonomy: none, shared, and full. Our findings indicate that fully automated systems can maintain conversational engagement, enabling users to multitask effectively. Surprisingly, shared autonomy hindered this ability. Based on our results, we discuss implications for designing shared autonomy in conversations, highlighting new considerations and challenges. © 2025 Copyright held by the owner/author(s).

关键词： computer-mediated communication

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DP-NMT: Scalable Differentially-Private Machine Translation 18

DP-NMT: Scalable Differentially-Private Machine Translation

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18th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2024

作者： Igamberdiev, Timour Vu, Doan Nam Long Künnecke, Felix Yu, Zhuo Holmer, Jannik Habernal, Ivan Trustworthy Human Language Technologies Department of Computer Science Technical University of Darmstadt Germany Trustworthy Human Language Technologies Department of Computer Science Paderborn University Germany

ISBN: (纸本)9798891760912

Neural machine translation (NMT) is a widely popular text generation task, yet there is a considerable research gap in the development of privacy-preserving NMT models, despite significant data privacy concerns for NMT systems. Differentially private stochastic gradient descent (DP-SGD) is a popular method for training machine learning models with concrete privacy guarantees;however, the implementation specifics of training a model with DP-SGD are not always clarified in existing models, with differing software libraries used and code bases not always being public, leading to reproducibility issues. To tackle this, we introduce DP-NMT, an open-source framework for carrying out research on privacy-preserving NMT with DP-SGD, bringing together numerous models, datasets, and evaluation metrics in one systematic software package. Our goal is to provide a platform for researchers to advance the development of privacy-preserving NMT systems, keeping the specific details of the DP-SGD algorithm transparent and intuitive to implement. We run a set of experiments on datasets from both general and privacy-related domains to demonstrate our framework in use. We make our framework publicly available and welcome feedback from the community. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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2D Skeleton-Based Keypoint Generation Method for Grasping Objects with Roughly Uniform Height Variation 11

2D Skeleton-Based Keypoint Generation Method for Grasping Ob...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Sabzejou, Ali Masouleh, Mehdi Tale Kalhor, Ahmad University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Department Iran

ISBN: (纸本)9798350308105

Robotic grasping poses a fundamental challenge in robotics, particularly when dealing with unknown objects. This skill has always been a focal point in robotics research due to its fundamental importance and inherent complexity. Recent advances utilize state-of-The-Art learning techniques, including deep learning and deep reinforcement learning, presenting their unique set of challenges. Training these models requires extensive data and computational resources, with the generalization to unknown objects presenting a significant obstacle for robots. This paper presents a comprehensive approach to unknown object robotic grasping, with a specific focus on top-down grasping actions. The process encompasses image preprocessing, the application of the Straight Skeleton (StSkel) method, and the systematic generation of grasp keypoints when applied to a selection of objects from the Dex-Net dataset. During the evaluation, the analysis incorporated crucial metrics, including the number of detected grasp keypoints for each object, the count of successfully generated grasp pairs, the overall success rate, and the success rate when considering the top 5 ranked grasp pairs. One of the notable strengths of this approach lies in its adaptability to a wide array of objects, ranging from simple shapes to complex ones. The proposed approach in this paper paves the way for automatically labeling grasping datasets, providing a valuable asset for developing auto-generating Deep-RL models. The StSkel method effectively captures essential structural information, making it suitable for real-world applications involving diverse objects. The experimental outcomes affirm the robustness and adaptability of the approach, as it most often achieved a high success rate in generating viable pairs of grasping points for most tested objects. Even complex objects yield impressive results, demonstrating the method's potential for real-world applications in grasping unknown objects. © 2023 IEEE.

关键词： Robotics

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Process hyper-relation knowledge graph construction and application 7

Process hyper-relation knowledge graph construction and appl...

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2024 7th International Conference on Intelligent Manufacturing and Automation, IMA 2024

作者： Lv, Yang Wang, Peiyan Ji, Guiyang Wang, Libang School of Computer Science Shenyang Aerospace University Shenyang110134 China Liaoning Prof. Technology Innovation Center on Knowledge Engineering and Human-Computer Interaction Shenyang110134 China

A knowledge graph enables the structured representation of process knowledge. Traditional knowledge graphs typically represent process fact knowledge by depicting relations between entities. However, higher-order knowledge, such as causality, coupling, and rationale among process facts, should be addressed. The Process Hyper-relational knowledge graph (PHKG) was proposed to address these shortcomings. It comprises three layers: a concept layer representing process concept knowledge, an instance layer representing process fact knowledge, and a hyper-relationship layer representing higher-order knowledge linking process facts. Employing a semi-automatic construction method, a hyper-relation knowledge graph was created with 1, 602 entities, 2, 509 entity relationships, and 231 pairs of hyper-relationships. A process knowledge reasoning algorithm has also been developed to enable applications to reason about process knowledge. © Published under licence by IOP Publishing Ltd.

关键词： Knowledge graph

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UI/UX Fundamental Design for Mobile Application Prototype to Support Web Accessibility and Usability Acceptance A Scenario-based Design of Mobile Application for Visually Impaired Users 23

UI/UX Fundamental Design for Mobile Application Prototype to...

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12th International Conference on Software and computer Applications, ICSCA 2023

作者： Jantan, Azrul Hazri Norowi, Noris Mohd Yazid, Mariam Azwa Faculty of Computer Science and Information Technology Universiti Putra Malaysia Malaysia Human-Computer Interaction Research Group Universiti Putra Malaysia Malaysia

ISBN: (纸本)9781450398589

User interface (UI) and user experience (UX) design is an evolving research topic that took up many attentions from researchers especially in software/web design processes. Effective UI/UX design could provide better navigational and accessibility support to access information;intuitive interaction processes to perform several tasks;and good users feedback/responses for its usability acceptance. In this article, we will discuss and overview the fundamental processes of constructing UI/UX design for mobile-based application which focusing on the interactions performed by visually impaired and blind (VIB) users. To meet our purpose, we worked together with the Malaysian Association for the Blind (MAB) to get valuable and useful information as part of the key input in this project. MAB is an association located in Brickfields, Kuala Lumpur that provide facilities and assistance for the People with Disabilities in the category of blindness. The main objective of this collaboration is to establish a strong communication and support between the Universiti Putra Malaysia (UPM) and the MAB in the context of technological support in ICT. We envisage the collaboration to provide better understanding and solutions to any current issues involving VIB users in digital world especially in information technology application and its environments. This article in general emphasizes the overall UI/UX design processes for mobile application prototype development which covered scenario-based activities and tasks among the VIB users. At the end of this article, we will discuss and summarize the best practice of the design steps and processes to provide effective user interface presentation to support better web accessibility and usability acceptance among VIB users. © 2023 Copyright held by the owner/author(s).

关键词： User interfaces

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Virtual Displays for Knowledge Work: Extending or Replacing Physical Monitors for More Flexibility and Screen Space

Virtual Displays for Knowledge Work: Extending or Replacing ...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Leonardo Pavanatto Doug A. Bowman Department of Computer Science Center for Human-Computer Interaction Virginia Tech USA

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374506

In this paper, we explore the potential of virtual displays in sup-porting knowledge work, focusing on scenarios where conventional physical monitors fall short. Our research investigates the feasibility and productivity costs of extending or replacing physical monitors with augmented and virtual reality displays. We present three com-pelling use cases, illustrating how virtual displays enhance flexibility, adaptability, and customization in remote and diverse work settings. Lessons learned from user studies highlight hardware and interface design challenges, emphasizing the need for larger resolution and field of view in head-worn displays (HWD). We conclude the paper with research opportunities and a call to address the evolving demands of knowledge work interfaces.

关键词： Productivity Three-dimensional displays Head-mounted displays Focusing Virtual reality User interfaces Hardware

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A Global Medical Data Security and Privacy Preserving Standards Identification Framework for Electronic Healthcare Consumers

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IEEE Transactions on Consumer Electronics 2024年第1期70卷 4379-4387页

作者： Mishra, Vinaytosh Gupta, Kishu Saxena, Deepika Singh, Ashutosh Kumar Thumbay Institute for Ai in Healthcare Gulf Medical University Ajman United Arab Emirates National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804 Taiwan The University of Aizu School of Computer Science and Engineering Aizuwakamatsu965 Japan University of Economics and Human Sciences Department of Computer Science Warsaw01-043 Poland Indian Institute of Information Technology Bhopal Department of Computer Science and Engineering Bhopal462003 India

Electronic Health Records (EHR) are crucial for the success of digital healthcare, with a focus on putting consumers at the center of this transformation. However, the digitalization of healthcare records brings along security and privacy risks for personal data. The major concern is that different countries have varying standards for the security and privacy of medical data. This paper proposed a novel and comprehensive framework to standardize these rules globally, bringing them together on a common platform. To support this proposal, the study reviews existing literature to understand the research interest in this issue. It also examines six key laws and standards related to security and privacy, identifying twenty concepts. The proposed framework utilized K-means clustering to categorize these concepts and identify five key factors. Finally, an Ordinal Priority Approach is applied to determine the preferred implementation of these factors in the context of EHRs. The proposed study provides a descriptive then prescriptive framework for the implementation of privacy and security in the context of electronic health records. Therefore, the findings of the proposed framework are useful for professionals and policymakers in improving the security and privacy associated with EHRs. © 1975-2011 IEEE.

关键词： K-means clustering

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Autonomous Unmanned Aerial Vehicle Indoor Navigation Based on Deep Learning Approaches 11

Autonomous Unmanned Aerial Vehicle Indoor Navigation Based o...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Ghasemi, Hamed Balazadeh, Elnaz Malekpour, Shayan Kalhor, Ahmad Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran University of Tehran Human and Robot Interaction Laboratory Tehran Iran University of Tehran School of Electrical and Computer Engineering Department of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350308105

This article presents two approaches based on deep learning for achieving autonomous navigation and subsequently, conducts an in-depth comparative analysis to elaborate their respective performance. Both methods leverage neural networks to facilitate navigation. The first approach employs a deep convolutional neural network to identify suitable areas for forward movement, while the second method utilizes the drone's front camera to capture images, which are then processed by a generative network to generate corresponding depth images. Importantly, both approaches rely solely on an RGB camera, resulting in cost savings for the robot and reduced energy consumption. The training data used for classifying collision-free and appropriate paths were gathered from simulated environments closely resembling real indoor settings. The proposed model calculates the probability associated with each segment of the input image, enabling the selection of the most viable area for drone flight. Incorporating generative networks as a depth estimation module enhances flight accuracy, making navigation in uncharted environments more straightforward. The accuracy of depth estimation was evaluated using standard criteria, achieving an accuracy rate of 84%. This result underscores the effectiveness of the proposed method. © 2023 IEEE.

关键词： Drones

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