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IEEE International Symposium on Mixed and Augmented Reality Workshops (ISMARW)

作者： Ioannis Safranoglou Alexis Stavroulakis Marcel Ebel Jens Pottebaum Georgios Lamprinakis Despina Dimelli Katerina Mania School of Electrical and Computer Engineering Technical University of Crete Paderborn University - Heinz Nixdorf Institute School of Architecture Technical University of Crete

ISBN: (数字)9798331506919

ISBN: (纸本)9798331506926

Locomotion interfaces for head-worn AR, while rescuers move on site, are critical in disaster response including flood emergency management. Incorporating live, real-time data, rather than static information, in the form of forecasting of events over time, without overloading the user’s field of view, is crucial. This paper presents an innovative head-worn AR flood management system designed to support situational awareness and way-finding by enhancing decision-making for emergency responders on-the-go. Our system dynamically visualizes present and predicted water levels as well as water speed and direction at specific future time intervals in real-time, regardless of location, improving flood management while rescuers are moving. Moreover, points of interest are shown in the horizon with the ones most likely to require assistance indicated by color variation, allowing rescuers to navigate and respond more effectively to emergency scenarios. Our gaze-enabled AR system prototype was tested by professional firefighters in Innsbruck and Dortmund. Feedback from these trials highlighted the potential of providing comprehensive, real-time, AR visualization to enhance disaster response strategies.

关键词： Visualization Three-dimensional displays Disasters Decision making Prototypes Emergency services Real-time systems Floods Augmented reality Resilience

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Quantitative Evaluation to Detect Crack Depth in Beams Based on CNN-RNN-LSTM Approach

Quantitative Evaluation to Detect Crack Depth in Beams Based...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Gandhi, Mohammad Asif Swaminathen, A.N. Patil, Deepak T. Ravitheja, A. Kamali, R. Rajput, Akshay Anjuman-I-Islam's Kalsekar Technical Campus Department of Mechanical Engineering Maharashtra Panvel India Adi Shankara Institute of Engineering and Technology Kerala India Bharati Vidyapeeth College of Architecture Maharashtra Navi Mumbai India Svr Engineering College Department of Civil Engineering Andhra Pradesh Kurnool India Knowledge Institute of Technology Department of Computer Science and Engineering Tamilnadu Salem India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350300857

In this study, the proposed approach offers a novel hybrid image-based deep learning method for autonomous concrete fracture identification. Cracks are easier to spot and false positives are reduced with hybrid images that include visual and infrared thermography data. In specifically, a Visible and infrared camera as well as a line laser make up a hybrid imaging system for spatially scanning unmanned vehicles can efficiently assess large-scale concrete-made constructions like bridges and dams. Crack detection is a commonplace task in many industrial domains, however the current method of relying on expert judgment is typically laborious, time consuming, and inaccurate. The practical benefits of automated decision-making increase as the size of the target concrete construction grows. Cracks can be automatically identified and seen using the proposed method. Preprocessing, segmentation, feature extraction, and model training are the four components of the proposed method. It performs clever edge recognition, scaling, and greyscale conversion as part of its preparation. Improved K-Means segmentation is used for the separation. It employs GLCM for feature extraction, and CNN-RNN-LSTM for model training. The new method is compared to two established approaches, CNN-RNN and CNN-LSTM, and is found to be superior. © 2023 IEEE.

关键词： Decision making

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Power-balanced Memristive Cryptographic Implementation Against Side Channel Attacks

arXiv

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arXiv 2023年

作者： Chen, Ziang Chen, Li-Wei Zhao, Xianyue Li, Kefeng Schmidt, Heidemarie Polian, Ilia Du, Nan Institute for Solid State Physics Friedrich Schiller University Jena Jena Germany Department of Quantum Detection Leibniz Institute of Photonic Technology Jena Germany Institute of Computer Science and Computer Engineering University of Stuttgart Stuttgart Germany

Memristors, as emerging nano-devices, offer promising performance and exhibit rich electrical dynamic behavior. Having already found success in applications such as neuromorphic and in-memory computing, researchers are now exploring their potential for cryptographic implementations. In this study, we present a novel power-balanced hiding strategy utilizing memristor groups to conceal power consumption in cryptographic logic circuits. Our approach ensures consistent power costs of all 16 logic gates in Complementary-Resistive-Switching-with-Reading (CRS-R) logic family during writing and reading cycles regardless of Logic Input Variable (LIV) values. By constructing hiding groups, we enable an effective power balance in each gate hiding group. Furthermore, experimental validation of our strategy includes the implementation of a cryptographic construction, xor4SBox, using NOR gates. The circuit construction without the hiding strategy and with the hiding strategy undergo T-test analysis, confirming the significant improvement achieved with our approach. Our work presents a substantial advancement in power-balanced hiding methods, offering enhanced security and efficiency in logic circuits. Copyright © 2023, The Authors. All rights reserved.

关键词： Memristors

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Modeling and Analysis of Virtualized Multi-Service Cloud Data Centers with Automatic Server Consolidation and Prescribed Service Level Agreements 23

Modeling and Analysis of Virtualized Multi-Service Cloud Dat...

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23rd International Conference on computer Theory and Applications, ICCTA 2013

作者： Mashaly, Maggie Kuehn, Paul J. German University in Cairo Information Engineering and Technology Department Cairo Egypt University of Stuttgart Institute of Communication Networks and Computer Engineering Stuttgart Germany

ISBN: (纸本)9781479924158

Cloud Data Centers (CDC) are developing rapidly and will have a major impact on IT infrastructures in the future for reasons of their low ramp-up costs and service delivery/support capabilities for the users. In this paper CDCs with multi-service application classes are considered which are operated under an automatic server consolidation based on parallel hysteresis methods for server activations/deactivations which have been reported on our previous work. Each class is subjected to an individual SLA, e.g., for the average service delay for non-real-time services or for delay percentiles for services with strict response time constraints, and probabilities for service rejection (loss) or migration. Operation of a CDC is modeled by Finite State Machine (FSM) - controlled queuing systems for each class of cloud services which are analyzed exactly under Markovian assumptions to receive averages and percentiles of response times and probabilities of loss or migration. The method is novel as it minimizes the energy consumption for servers by an automatic server consolidation strategy while guaranteeing the negotiated SLAs. The method is based on a worst case boundary consideration for the delays of arriving service requests and can be useful to understand the parametric influences and to assess the energy saving gains for multi-tier CDCs. © 2013 IEEE.

关键词： Energy utilization

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Tunable Multicolor Fluorescence of Perovskite-Based Composites for Optical Steganography and Light-Emitting Devices

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Research 2023年第1期2022卷 185-195页

作者： Kewei Ma Qingfeng Gui Cihui Liu Yunyi Yang Fangjian Xing Yunsong Di Xiaoming Wen Baohua Jia Zhixing Gan Center for Future Optoelectronic Functional Materials School of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing 210023China College of Naval Architecture and Ocean Engineering Jiangsu Maritime InstituteNanjing 211170China Centrefor Translational Atomaterials Schoolof ScienceSwinburne University of TechnologyJohn Street Hawthon VIC3122Australia School of Science RMIT UniversityMelbourne3000 VICAustralia College of Materials Science and Engineering Qingdao University of Science and TechnologyQingdao 266042China

Multicolor fluorescence of mixed halide perovskites enormously enables their applications in photonics and ***,it remains an arduous task to obtain multicolor emissions from perovskites containing single halogen to avoid phase ***,a fluorescent composite containing Eu-based metal-organic frameworks(MOFs),OD Cs PbBre,and 3D CsPbBrs is *** excitations at 365 nm and 254nm,the pristine composite emits blue(B)and red(R)fluorescence,which are ascribed to radiative defects within CsPbBr and 5Do→7F,transitions of Eu^(3+),***,after light soaking in the ambient environment,the blue fluorescence gradually converts into green(G)emission due to the defect repairing and 0D-3D phase *** permanent and unique photochromic effect enables anticounterfeiting and microsteganography with increased security through a micropatterning ***,the RGB luminescence is highly stable after encapsulation by a transparent polymer ***,trichromatic light-emitting modules are fabricated by using the fluorescent composites as color-converting layers,which almost fully cover the standard color ***,this work innovates a strategy for construction of tunable multicolor luminescence by manipulating the radiative defects and structural dimensionality.

关键词： composite composites perovskite

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Exploring Children’s Strategies in Response to Robot’s Advice During a Group Task with iCub and Nao 16th

Exploring Children’s Strategies in Response to Robot’s A...

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16th International Conference on Social Robotics, ICSR + AI 2024

作者： Pusceddu, Giulia Sangineto, Mariapia Cocchella, Francesca Bogliolo, Michela Belgiovine, Giulia Lastrico, Linda Casadio, Maura Rea, Francesco Gena, Cristina Sciutti, Alessandra Robotics Brain and Cognitive Science Department Italian Institute of Technology Genoa Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Department of Computer Science University of Turin Turin Italy Cognitive Architecture for Collaborative Technologies Unit Italian Institute of Technology Genoa Italy Scuola di Robotica Genoa Italy

ISBN: (纸本)9789819635184

This study investigates children’s trust in two humanoid robots, Nao and iCub, through a cooperative game designed to elicit spontaneous behaviors and group dynamics. We investigate whether participants change their choices after hearing advice from a robot, considering rounds where the advice is correct or incorrect, with the robot apologizing for its mistakes. Results reveal that, in most cases, participants prefer not to change their moves after the robot’s advice. Additionally, after the robots made mistakes, participants are less likely to actively follow their advice and more likely to reject it. No significant differences in strategies among the iCub and Nao samples are evidenced. Furthermore, we examine the influence of group dynamics, identifying "Proactive Players" who consistently initiated moves. A significant association between the strategies of this player and their teammates is found, suggesting potential influence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Data Availability Optimization for Cyber-Physical Systems 15

Data Availability Optimization for Cyber-Physical Systems

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2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green Computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th IEEE International Conference on Smart Data, SmartData 2022

作者： Li, Liying Cong, Peijin Zhou, Junlong Gu, Zonghua Li, Keqin School of Computer Science and Engineering Nanjing University of Science and Technology China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Department of Applied Physics and Electronics Ume˚a University Sweden Department of Computer Science State University of New York United States

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

As the backbone of Industry 4.0, Cyber-Physical Systems (CPSs) have attracted extensive attention from industry, academia, and government. Missing data is a common problem in CPS data processing and may cause incorrect results and eventually serious malfunction. Existing data availability optimization methods either rely on a large amount of complete training data or suffer from poor performance. To solve these problems, this paper proposes an iterative data availability optimization method for CPSs. Specifically, the proposed method first pre-processes the raw dataset by using a Singular Value Decomposition-based feature selection approach to identify crucial features and reduce computation overheads. It then makes an initial guess for missing values via a designed K-Means-based imputation approach. The appropriate initial estimation decreases the probability of the proposed method falling into the local optimum. Finally, the proposed method iteratively estimates missing data based on the Orthogonal Matching Pursuit algorithm. The proposed method optimizes data availability by accurately imputing missing values. Simulation results on two datasets demonstrate that compared to multiple state-of-the-art approaches, the proposed data availability optimization method can reduce imputation error by up to 99.65%. © 2022 IEEE.

关键词： Iterative methods

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An Online Integrated Development Environment for Automated Programming Assessment Systems

arXiv

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arXiv 2025年

作者： Frankford, Eduard Crazzolara, Daniel Vierhauser, Michael Meißner, Niklas Krusche, Stephan Breu, Ruth University of Innsbruck Department of Computer Science Austria University of Stuttgart Institute of Software Engineering Germany Technical University of Munich School of Computation Information and Technology Germany

The increasing demand for programmers has led to a surge in participants in programming courses, making it increasingly challenging for instructors to assess student code manually. As a result, automated programming assessment systems (APASs) have been developed to streamline this process. These APASs support lecturers by managing and evaluating student programming exercises at scale. However, these tools often do not provide feature-rich online editors compared to their traditional integrated development environments (IDEs) counterparts. This absence of key features, such as syntax highlighting and autocompletion, can negatively impact the learning experience, as these tools are crucial for effective coding practice. To address this gap, this research contributes to the field of programming education by extracting and defining requirements for an online IDE in an educational context and presenting a prototypical implementation of an open-source solution for a scalable and secure online IDE. The usability of the new online IDE was assessed using the Technology Acceptance Model (TAM), gathering feedback from 27 first-year students through a structured survey. In addition to these qualitative insights, quantitative measures such as memory (RAM) usage were evaluated to determine the efficiency and scalability of the tool under varying usage conditions. © 2025, CC BY-NC-ND.

关键词： Students

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OntoBlock: a novel ontological-based and blockchain enabled spectrum sensing framework for detection of malicious users in cognitive radio internet of things (CR-IoT) networks

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International Journal of Information Technology (Singapore) 2024年第6期16卷 3913-3921页

作者： Marriwala, Nikhil Kumar Shukla, Vinod Kumar Raju, Ayalapogu Ratna Panda, Sunita S, Suma Purad, Hemavati C. Electronics and Communication Engineering Department University Institute of Engineering and Technology Kurukshetra University Haryana Kurukshetra India Information Technology Head of Academics–School of Engineering Architecture Interior Design Amity University Dubai Dubai International Academic City Dubai United Arab Emirates Department of Computer Science and Engineering Mahatma Gandhi Institute of Technology Hyderabad India Department of Electrical Electronics and Communication Engineering GITAM School of Technology Bengaluru Campus Karnataka Bengaluru India CMR Technical Campus Hyderabad India Department of AIML BITM Karnataka Ballari India

CR-IoT networks can benefit from the idea of blockchain technology to achieve accurate decisions in order to provide very high-accuracy spectrum sensing in the network. It allows for multi-user cooperation as the sensing readings are being exchanged in the spectrum. It leads to security issues in CR-IoT networks. Thus, in order to increase the quality of decision-making in spectrum sensing, the given paper introduces an ontological framework with a blockchain-enabled system to detect malicious users in networks. The proposed framework first captures network packets from available Wi-Fi, followed by the creation of blocks with private, public, and hash keys. The keys are used to encode information about the nodes, such as confidential information and their location, data relative to users, their position where packets are delivered, etc. This is subsequently followed by the generation of network ontology, which includes parsing, computation of similarity, and reduction in clustered packets. Finally, the performance of the suggested mechanism is validated using a set of evaluation measures such as authentication rate, intrusion rate, average network throughput time consumption, and energy efficiency. As seen from the findings, it is evident that the proposed framework performs better than existing recent studies, thereby improving the performance of CR-IoT networks. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Blockchain Cognitive radio Internet of things (IoT) Ontology Spectrum sensing

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Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention

arXiv

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arXiv 2024年

作者： Demmler, Tobias Tamke, Andreas Dang, Thao Haug, Karsten Mikelsons, Lars Robert Bosch GmbH Stuttgart Germany The Institute for Intelligent Systems Department of Computer Science and Engineering Esslingen University Germany The University of Augsburg Germany

In autonomous driving, accurately interpreting the movements of other road users and leveraging this knowledge to forecast future trajectories is crucial. This is typically achieved through the integration of map data and tracked trajectories of various agents. Numerous methodologies combine this information into a singular embedding for each agent, which is then utilized to predict future behavior. However, these approaches have a notable drawback in that they may lose exact location information during the encoding process. The encoding still includes general map information. However, the generation of valid and consistent trajectories is not guaranteed. This can cause the predicted trajectories to stray from the actual lanes. This paper introduces a new refinement module designed to project the predicted trajectories back onto the actual map, rectifying these discrepancies and leading towards more consistent predictions. This versatile module can be readily incorporated into a wide range of architectures. Additionally, we propose a novel scene encoder that handles all relations between agents and their environment in a single unified heterogeneous graph attention network. By analyzing the attention values on the different edges in this graph, we can gain unique insights into the neural network’s inner workings leading towards a more explainable prediction. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

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