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arXiv 2022年

作者： Hemathilaka, Susith Aponso, Achala Department of Computer Science and Software Engineering University of Westminster London United Kingdom Department of Computer Science Informatics Institute of Technology Colombo Sri Lanka

The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face, and it makes it difficult to recognize them even for humans. The evaluation report shows the difficulty well when recognizing masked faces. Rapid development and breakthrough of deep learning in the recent past have witnessed most promising results from face recognition algorithms. But they fail to perform far from satisfactory levels in the unconstrained environment during the challenges such as varying lighting conditions, low resolution, facial expressions, pose variation and occlusions. Facial occlusions are considered one of the most intractable problems. Especially when the occlusion occupies a large region of the face because it destroys lots of official features. © 2022, CC BY.

关键词： Face recognition

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Unsupervised Fact-Checking via Recursively Verifying Presuppositions

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 2189-2199页

作者： Xiucheng Lyu Runcong Zhao Jiazheng Li Bin Liang Min Yang Lin Gui Ruifeng Xu School of Computer Science and Technology Harbin Institute of Technology (Shenzhen) Shenzhen China Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Shenzhen China Department of Informatics King’s College London London U.K. Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong SAR China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Peng Cheng Laboratory Shenzhen China

Presuppositions are implicit assumptions that interlocutors take for granted. Verifying presuppositions is crucial for reasoning-based fact-checking that aims to reason about True or False, but existing pipelines have overlooked it. We first raise this critical issue with the community and propose a system that addresses the generation, verification, and reasoning of presuppositions through a recursive question-answering process. Importantly, our system automatically determines which knowledge entails which presuppositions, making it an unsupervised system for evidence retrieval, fact-checking, and justification production. We conduct a comprehensive experiment on the FEVER, Vitamin C, and FEVEROUS-S datasets. Our system outperforms competitive baselines, including LLM, and achieves state-of-the-art unsupervised performance. We highlight this critical issue to encourage further research on reasoning-based fact-checking.

关键词： Cognition Training Speech processing Pipelines Electronic mail Production Semantics Tree traversal Security Reliability

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Transforming Experimental Cobot Cell to Industrial Realization – an Ethical AI Approach

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IFAC-PapersOnLine 2023年第2期56卷 7335-7341页

作者： Istvan Mezgár József Váncza Imre Paniti József Tóth EPIC Center of Excellence in Production Informatics and Control Institute for Computer Science and Control Budapest Hungary Department of Manufacturing Science and Technology Budapest University of Technology and Economics Budapest Hungary Hepenix Ltd. Diósd Hungary

Collaborative Robot (cobot) cells are getting more and more integrative building blocks of Cyber Physical Enterprises. These cells integrate the advantages of human workers with the special capabilities of robots in a safe manner. Cobots need advanced, in many cases artificial intelligence (AI) based control systems to harmonize the collaborative activities. When transferring/transforming experimental setups into industrial application, not only technological and business related, but also ethical aspects have to be taken into consideration. The paper introduces a novel workflow supporting this transformation and presents its application in a case-study of a cobot cell which uses advanced sensing, symbolic AI planning and mixed reality techniques for planning and explaining visually the operation of the cell. The work which takes the responsible artificial intelligence (RAI) approach combines the actual relevant AI standards with the explicit requirements of industrial practitioners.

关键词： Collaborative robotics Artificial intelligence Ethics Design methodology

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The Implementation of TOGAF for Enterprise System Planning on XYZ Campus

The Implementation of TOGAF for Enterprise System Planning o...

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Networking, Electrical Engineering, computer Science, and technology (IConNECT), International Conference on

作者： Tamsir Hasudungan Sirait Ford Lumban Gaol Suhono Harso Supangkat Benny Ranti Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Computer Science Department Universitas Indonesia Jakarta Indonesia

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology.

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Comparative Analysis of Laboratory and Radiation Methods of Studies with the Degree of Severity of Patients with COVID-19 25

Comparative Analysis of Laboratory and Radiation Methods of ...

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25th International Conference on Digital Signal Processing and its Applications, DSPA 2023

作者： Kents, Angelica Zotin, Aleksandr Simonov, Konstantin Center for Radiation Diagnostics Federal Siberian Research and Clinical Center of Fmba of Russia X-ray Department Krasnoyarsk Russia Reshetnev Siberian State University of Science and Technology Candidate of Technical Sciences Department of Informatics and Computer Techniques Krasnoyarsk Russia Institute of Computational Modeling Sb Ras Doctor of Technical Sciences Department of Computational Mechanics of Deformable Media Krasnoyarsk Russia

ISBN: (纸本)9798350337235

The study is devoted to a comparative analysis and retrospective evaluation of laboratory and instrumental data with the severity of lung tissue damage in COVID-19 of patients with COVID-19. An improvement was made in the methodology for interpreting and analyzing dynamic changes associated with COVID-19 on CT images of the lungs. The technique includes the following steps: pre-processing, segmentation with color coding, calculation and evaluation of signs to highlight areas with probable pathology (including combined evaluation of signs). Analysis and interpretation is carried out on the emerging database of patients. At the same time the following indicators are distinguished: the results of the analysis of CT images of the lungs in dynamics;the results of the analysis of clinical and laboratory data (severity course of the disease, temperature, saturation, etc.). The results of laboratory studies are analyzed with an emphasis on the values of the main indicator - interleukin-6. This indicator is a marker of significant and serious changes characterizing the severity of the patient's condition. © 2023 IEEE.

关键词： COVID-19

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Exploration of the Role of Cryptoprocessors in Advancing IoT Security

Exploration of the Role of Cryptoprocessors in Advancing IoT...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Elena Kakoulli Eleftherios Zacharioudakis Department of Computer Science Intelligent Systems Laboratory Neapolis University Pafos Pafos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Igor Sikorsky Kyiv Polytechnic Institute National Technical University of Ukraine Kyiv Ukraine

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

This paper presents a thorough exploration of Cryptoprocessors in the context of the Internet of Things (IoT). The focus is on hardware support, cryptographic processors, and energy-efficient designs to fortify the security of IoT ecosystems. Leveraging insights from recent research papers, the survey examines various aspects of Cryptoprocessor implementations, ranging from lightweight countermeasures to advanced lattice-based post-quantum cryptography. The proposed paper amalgamates findings from studies on hardware architectures, energy-efficient designs, and innovative cryptographic algorithms to provide a holistic overview of state-of-the-art advancements in IoT security. The synthesis of this survey’s exploration aims to contribute to the ongoing discourse on securing IoT devices through robust hardware-backed cryptographic solutions.

关键词： Surveys Industries Technological innovation Program processors Ecosystems Hardware Energy efficiency

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Piloting Systematic Implementation of Educational technology in Swedish K-12 Schools – Two-Years-In Report

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Global Implementation Research and Applications 2024年第3期4卷 309-323页

作者： Nordmark, Susanna Augustsson, Hanna Davidsson, Mattias Andersson-Gidlund, Tobias Holmberg, Kristina Mohseni, Zeynab (Artemis) Rack, John Masiello, Italo Department of Computer Science and Media Technology Linnaeus University Växjö Sweden Department of Learning Informatics Management and Ethics Karolinska Institute Stockholm Sweden Department of Education and Teachers’ Practice Linnaeus University Växjö Sweden Department of Pedagogy and Learning Linnaeus University Växjö Sweden

Halfway through a four-year research project supported by implementation science and the Active Implementation Frameworks (AIF), this article reports on the status of the initial two implementation stages. Our research investigates the impact of systematically preparing educators and educational institutions to integrate digital learning materials and learning analytics dashboards to enrich teaching practices and improve student performance outcomes. Furthermore, it seeks to establish a foundation for the use of innovative and validated educational technology (EdTech) through sustainable implementation strategies, evidence-based evaluation, and continuous redesign of digital learning materials. By adopting this comprehensive approach, we aim to enhance the knowledge base regarding effective digital innovation integration within educational environments. We argue that applying implementation science in educational settings facilitates the adoption of effective innovations, promotes evidence-based decision-making, and helps identify and address obstacles to change. Our ongoing research underscores the transformative impact of implementation science in education. Thus far, we have highlighted the crucial role of teacher perspectives and the necessity of co-designing technology aligned with teaching and learning objectives. This nuanced approach refutes the notion of a one-size-fits-all solution or a quick fix achievable in a single academic year. Instead, it advocates a dynamic, collaborative model that acknowledges the multifaceted nature of implementation. Our journey has reaffirmed the dedication of teachers, showcasing their readiness to invest time and effort when their professionalism is respected, and their input is genuinely valued and acted upon.

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A multilevel paradigm for deep convolutional neural network features selection with an application to human gait recognition

A multilevel paradigm for deep convolutional neural network ...

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作者： Arshad, Habiba Khan, Muhammad Attique Sharif, Muhammad Irfan Yasmin, Mussarat Tavares, João Manuel R. S. Zhang, Yu-Dong Satapathy, Suresh Chandra Department of Computer Science COMSATS University Islamabad Islamabad Pakistan Department of Computer Science HITEC University Taxila Pakistan School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial Departamento de Engenharia Mecânica Faculdade de Engenharia Universidade do Porto Porto Portugal Department of Informatics University of Leicester Leicester United Kingdom School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India

Human gait recognition (HGR) shows high importance in the area of video surveillance due to remote access and security threats. HGR is a technique commonly used for the identification of human style in daily life. However, many typical situations like change of clothes condition and variation in view angles degrade the system performance. Lately, different machine learning (ML) techniques have been introduced for video surveillance which gives promising results among which deep learning (DL) shows best performance in complex scenarios. In this article, an integrated framework is proposed for HGR using deep neural network and fuzzy entropy controlled skewness (FEcS) approach. The proposed technique works in two phases: In the first phase, deep convolutional neural network (DCNN) features are extracted by pre-trained CNN models (VGG19 and AlexNet) and their information is mixed by parallel fusion approach. In the second phase, entropy and skewness vectors are calculated from fused feature vector (FV) to select best subsets of features by suggested FEcS approach. The best subsets of picked features are finally fed to multiple classifiers and finest one is chosen on the basis of accuracy value. The experiments were carried out on four well-known datasets, namely, AVAMVG gait, CASIA A, B and C. The achieved accuracy of each dataset was 99.8, 99.7, 93.3 and 92.2%, respectively. Therefore, the obtained overall recognition results lead to conclude that the proposed system is very promising. © 2020 John Wiley & Sons, Ltd.

关键词： Convolutional neural networks

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Radiance Field Delta Video Compression in Edge-Enabled Vehicular Metaverse

arXiv

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arXiv 2024年

作者： Dopiriak, Matúš Šlapak, Eugen Gazda, Juraj Gurjar, Devendra S. Faruque, Mohammad Abdullah Al Levorato, Marco Department of Computers and Informatics Technical University of Košice Slovakia Department of Electronics and Communications Engineering National Institute of Technology Silchar India Department of Electrical Engineering and Computer Science University of California Irvine United States

Connected and autonomous vehicles (CAVs) offload computationally intensive tasks to multi-access edge computing (MEC) servers via vehicle-to-infrastructure (V2I) communication, enabling applications within the vehicular metaverse, which transforms physical environment into the digital space enabling advanced analysis or predictive modeling. A core challenge is physical-to-virtual (P2V) synchronization through digital twins (DTs), reliant on MEC networks and ultra-reliable low-latency communication (URLLC). To address this, we introduce radiance field (RF) delta video compression (RFDVC), which uses RF-encoder and RF-decoder architecture using distributed RFs as DTs storing photorealistic 3D urban scenes in compressed form. This method extracts differences between CAV-frame capturing actual traffic and RF-frame capturing empty scene from the same camera pose in batches encoded and transmitted over the MEC network. Experiments show data savings up to 71% against H.264 codec and 44% against H.265 codec under different conditions as lighting changes, and rain. RFDVC also demonstrates resilience to transmission errors, achieving up to +0.29 structural similarity index measure (SSIM) improvement at block error rate (BLER) = 0.35 in non-rainy and +0.25 at BLER = 0.2 in rainy conditions, ensuring superior visual quality compared to standard video coding (VC) methods across various conditions. Copyright © 2024, The Authors. All rights reserved.

关键词： Image compression

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The Goofus & Gallant Story Corpus for Practical Value Alignment

arXiv

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arXiv 2025年

作者： Nahian, Md Sultan Al Tasrin, Tasmia Frazier, Spencer Riedl, Mark Harrison, Brent Institute for Biomedical Informatics University of Kentucky LexingtonKY United States Department of Computer Science University of Kentucky LexingtonKY United States School of Interactive Computing Georgia Institute of Technology AtlantaGA United States

Values or principles are key elements of human society that influence people to behave and function according to an accepted standard set of social rules to maintain social order. As AI systems are becoming ubiquitous in human society, it is a major concern that they could violate these norms or values and potentially cause harm. Thus, to prevent intentional or unintentional harm, AI systems are expected to take actions that align with these principles. Training systems to exhibit this type of behavior is difficult and often requires a specialized dataset. This work presents a multi-modal dataset illustrating normative and non-normative behavior in real-life situations described through natural language and artistic images. This training set contains curated sets of images that are designed to teach young children about social principles. We argue that this is an ideal dataset to use for training socially normative agents given this fact. © 2025, CC BY.

关键词： Adversarial machine learning

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