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13th International Winter Conference on Brain-computer Interface, BCI 2025

作者： Lee, Chaewon Lee, Sunho Annen, Jitka Jeong, Ji-Hoon Massimini, Marcello Casarotto, Silvia Boly, Melanie Bodart, Olivier Thibaut, Aurore Rosanova, Mario Laureys, Steven Gosseries, Olivia Lee, Minji Dept. Data Science The Catholic University of Korea Bucheon Korea Republic of Dept. Biomedical Software Engineering The Catholic University of Korea Bucheon Korea Republic of Dept. GIGA-Research & Neurology University and University Hospital of Liege Liege Belgium Dept. Data Analysis University of Ghent GhentB9000 Belgium Dept. Computer Science Chungbuk National University Cheongju Korea Republic of Dept. Biomedical and Clinical Sciences "L. Sacco" University of Milan Milan Italy Wisconsin Institute for Sleep and Consciousness Dept. Psychiatry University of Wisconsin Madison United States Coma Science Group GIGA-Consciousness GIGA Research Center University of Liège Liège Belgium Centre du Cerveau Neurology department University Hospital of Liège Liège Belgium

ISBN: (纸本)9798331521929

Advances in intensive care have improved the survival rate of patients with severe acute brain injury, but diagnostic errors for patients with disorders of consciousness are still high. Accurate diagnosis of these patients is very important because effective treatment can vary depending on the diagnosis. In this study, we propose a framework for classifying unresponsive wakefulness syndrome and minimally conscious state, focusing on awareness. In particular, power spectral density and common spatial patterns were used together, considering that spatial information is a key feature in consciousness. The 16 patients with unresponsive wakefulness syndrome and 14 with minimally conscious state underwent resting-state electroencephalography measurements. In addition, we compared the performance by utilizing each frequency (delta, theta, alpha, beta, gamma bands) related to consciousness. As a result, the highest accuracy of 95.06% was achieved by the EEGNet classifier, especially in the beta frequency band. We demonstrated that spatial information is very important in consciousness, as we observed that classification performance improved when common spatial patterns were used. These results provide insight into various frameworks for diagnosing patients with disorders of consciousness and may help patients survive by increasing the diagnosis rate in the future. © 2025 IEEE.

关键词： Electroencephalography

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LOCCAM - Loosely coupled context acquisition middleware 13

LOCCAM - Loosely coupled context acquisition middleware

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28th Annual ACM Symposium on Applied Computing, SAC 2013

作者： Maia, Marcio E.F. Fonteles, Andre Neto, Benedito Gadelha, Romulo Viana, Windson Andrade, Rossana M.C. Group of Computer Networks Software Engineering and Systems Federal University of Ceara Fortaleza Brazil

ISBN: (纸本)9781450316569

Sensors of all kinds are being integrated with mobile and portable devices (tablets, smartphones). This opens up the possibility of context-aware applications to effectively be able to adapt their behavior, user interfaces and content according to the current user's situation. Frequently, context-aware applications require an infrastructure for acquisition, aggregation and reasoning of contextual information. However, existing context management infrastructures are not always appropriated to the heterogeneous and particular environment of mobile devices. In this paper, we present a context management middleware called LoCCAM (Loosely Coupled Context Acquisition Middeware) to provide self-adaptive acquisition of contextual information. It can execute both locally, on a single device, or distributed among nearby devices. The middleware proposes a model for publication, and notification of contextual information based on tuple spaces. As consequence, it offers a lower coupling among applications and the context acquisition layer. In this paper, we also present a performance evaluation of the adaptation mechanism. Copyright 2013 ACM.

关键词： Middleware

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Implicit Multi-Scale Swin Transformer Network for Image Denoising

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IEEE Transactions on Consumer Electronics 2025年

作者： Zhang, Qi Ding, Yuwei Zhang, Weiqi Zhu, Yian Zhang, Bob Lin, Jerry Chun-Wei Harbin Institute of Technology at Weihai School of Economics and Management Weihai China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China Northwestern Polytechnical University School of Computer Science Xi’an China Northwestern Polytechnical University Yangtze River Delta Research Institute Taicang China University of Macau PAMI Research Group Department of Computer and Information Science Taipa China Department of Distributed Systems and IT Devices Electrical Engineering and Mathematical Sciences Silesian university of technology Poland

Image denoising has been used in various edge computing scenarios such as consumer electronics to improve the image quality and user experience. Existing image denoising methods based on Convolutional Neural networks (CNNs) and vision Transformers achieve good performance by empirically utilizing residual neural network (ResNet) as basic component. However, ResNet lacks interpretability in network design and also long-term memory of features, potentially restricting the performance of denoising networks. In this paper, we propose an Implicit Multi-scale Swin Transformer Network (IMSNet) for image denoising, which introduces the implicit Euler scheme from the feature memory perspective. Specifically, densely connected implicit feature extraction blocks (IFEBs) are designed to learn the residual mapping between noisy and clean images. The IFEB reformulates the initial skip connection of ResNet based on the implicit Euler discretization, providing both network interpretability and long-term memory. In IFEB, the multi-scale swin Transformer block (MSB) is designed as the implicit layer to capture spatial details and non-local contextual information at different scales. Additionally, a cross-layer feature fusion block (CLFF) is proposed to further improve feature reuse capabilities. Compared to existing denoising networks, the extensive experiments demonstrate the superior performance of our IMSNet in various image denoising tasks, and the flexibility in the practical applications with proposed light model on resource-restricted platforms such as consumer electronic devices. © 1975-2011 IEEE.

关键词： Image denoising

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Measuring technology effects on software change cost

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BELL LABS TECHNICAL JOURNAL 2000年第2期5卷 7-18页

作者： Atkins, DL Mockus, A Siy, HP Software Production Research Department Bell Labs Eugene Oregon Software Production Research Department Bell Labs Naperville Illinois Switching Architecture Performance and Engineering Department Lucent's Service Provider Networks Group Naperville Illinois

We describe a methodology for precise quantitative measurement of technology impact on software change effort. The methodology employs measures of small software changes to determine the effect of technology. We illustrate this approach in a detailed case study on the impact of using two particular technologies-a version-sensitive source code editor and a domain-engineered application environment-in a telecommunications product In both cases, the change effort was reduced. The methodology can precisely measure cost savings in change effort and is simple and inexpensive, since it relies on information automatically collected by Version control systems.

关键词： software engineering

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Framework for building intelligent mobile social applications 12

Framework for building intelligent mobile social application...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Maia, Marcio E. F. Filho, Joao Bosco F. Filho, Carlos A. B. De Q. Castro, Rute N. S. Andrade, Rossana M. C. Toorn, Fredrik De Aguiar, Saulo Bezerra Mateus, Bruno Gois Group of Computer Networks Software Engineering and Systems - GREat Federal University of Ceará Quixadá Ceará Brazil Group of Computer Networks Software Engineering and Systems - GREat Federal University of Ceará Fortaleza Ceará Brazil Sony Ericsson Brazil

ISBN: (纸本)9781450308571

The use of online social networks (OSN) has been a reality for some years now. If OSN users have mobile devices and they are taken into account, every day a vast amount of information is spontaneously generated, creating opportunities for researchers and developers to use, for example, artificial intelligent techniques to explore similarities between friends, to recommend content and to come up with business opportunities. Additionally, OSN and mobile devices can be put together to explore user context to tailor services according to the user environment. However, to apply ubiquitous computing and artificial intelligence to OSN can be cumbersome and resource-consuming. Thus, this paper presents a framework to develop intelligent applications on top of existing OSN, helping developers to explore similarities between the users and recommend content, using user context and simple information present on OSN, without compromising resources present in mobile devices. At the end, this paper shows how to develop new applications using the framework exploring user context and semantic concepts defined by the developer. © 2012 ACM.

关键词： Social networking (online)

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Event-driven bi-fidelity control for efficient and reliable robotic manipulation

Results in Engineering

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Results in engineering 2025年 26卷

作者： Fawaz W. Alsaade Mohammed S. Al-zahrani Fuad E. Alsaadi Department of Computer Science College of Computer Sciences and Information Technology King Faisal University Al-Ahsa 31982 Saudi Arabia Department of Computer Networks and Communications College of Computer Sciences and Information Technology King Faisal University Al-Ahsa 31982 Saudi Arabia Communication Systems and Networks Research Group Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia

This paper proposes a novel bi-fidelity control framework for robotic manipulators that integrates a high-fidelity model predictive control (MPC) scheme with a low-fidelity Long Short-Term Memory (LSTM) neural network surrogate. Unlike conventional fixed-schedule approaches, our method employs an event-triggered mechanism that dynamically selects the appropriate controller based on a real-time error metric. This mechanism ensures that the computationally intensive MPC is invoked only when the LSTM approximation deviates beyond acceptable bounds. We rigorously established the near-optimal performance and closed-loop stability of our approach via Lyapunov analysis under mild assumptions, instilling confidence in its reliability. The simulation results on a three-arm manipulator, subject to low-frequency sinusoidal and high-frequency chirp trajectories, demonstrate that the proposed approach achieves up to 80–90% reduction in MPC calls, significantly improving the accuracy of the follow-up and computational efficiency. These findings highlight the potential of integrating learning-based approximations with conventional optimization-based control to achieve reliable and time-efficient performance in complex robotic manipulation tasks.

关键词： Bi-fidelity control Optimal control LSTM neural networks Event-triggered control Robotic manipulator Hybrid control systems

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Track and Trace: Automatically Uncovering Cross-chain Transactions in the Multi-blockchain Ecosystems

arXiv

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arXiv 2025年

作者： Lin, Dan Zheng, Ziye Wu, Jiajing Yang, Jingjing Lin, Kaixin Xiao, Huan Song, Bowen Zheng, Zibin School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China School of Software Engineering Sun Yat-sen University Zhuhai519082 China GuangDong Engineering Technology Research Center the School of Software Engineering Guizhou University Guiyang550025 China Ant Group Hangzhou China

Cross-chain technology enables seamless asset transfer and message-passing within decentralized finance (DeFi) ecosystems, facilitating multi-chain coexistence in the current blockchain environment. However, this development also raises security concerns, as malicious actors exploit cross-chain asset flows to conceal the provenance and destination of assets, thereby facilitating illegal activities such as money laundering. Consequently, the need for cross-chain transaction traceability has become increasingly urgent. Prior research on transaction traceability has predominantly focused on single-chain and centralized finance (CeFi) cross-chain scenarios, overlooking DeFi-specific considerations. This paper proposes ABCTRACER, an automated, bi-directional cross-chain transaction tracing tool, specifically designed for DeFi ecosystems. By harnessing transaction event log mining and named entity recognition techniques, ABCTRACER automatically extracts explicit cross-chain cues. These cues are then combined with information retrieval techniques to encode implicit cues. ABCTRACER facilitates the autonomous learning of latent associated information and achieves bidirectional, generalized cross-chain transaction tracing. Our experiments on 12 mainstream cross-chain bridges demonstrate that ABCTRACER attains 91.75% bi-directional traceability (F1 metrics) with self-adaptive capability. Furthermore, we apply ABCTRACER to real-world cross-chain attack transactions and money laundering traceability, thereby bolstering the traceability and blockchain ecological security of DeFi bridging applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Blockchain

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Quantum qubit-optical cavity node: Effects of the temperature and coupling strengths on the cavity Fock-state distribution occupation probability and entropy of the subsystems using Dicke model

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Results in Physics 2025年 72卷

作者： Barhoumi, Mohamed Bassoli, Riccardo Fitzek, Frank H.P. Laboratory of Condensed Matter and Nanosciences (LMCN) Department of Physics Faculty of Sciences of Monastir University of Monastir Environment Street Monastir 5019 Tunisia Institut Supérieur d'Informatique et de Mathématiques de Monastir (ISIMM) University of Monastir Avenue de la Corniche Monastir 5000 Tunisia Deutsche Telekom Chair of Communication Networks Institute of Communication Technology Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden Germany Centre for Tactile Internet with Human-in-the-Loop (CeTI) Cluster of Excellence Dresden Germany Quantum Communication Networks (QCNets) research group Institute of Communication Technology Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden Germany

One of the most attractive systems for scalable quantum processing is the trapped atom in the optical cavity, which is easily manipulable with lasers. The qubit cavity system represents an attractive structure for quantum optics, with possibilities for applications in quantum detecting, quantum computation, and quantum communication. In addition, the investigation of the cavity-atom system under temperature is a fundamental concept in quantum optics and quantum information science. Here we continue in this quantum way, investigating different qubit(s)-cavity systems (where we increase the numbers of the qubit inside the optical cavity from one to four). Using the Dicke model, we calculate the probability of occupation of the ground state of the cavity 〈aˆ^†aˆ〉 and the expectation values 〈J_z〉 for each system. We find that these probabilities increase as the coupling strength C_s increases. This leads to reaching the ultra-strong coupling regime, which depends on the number of qubits. To describe the quantum state, we examine the cavity Wigner function WF as a function of the coupling strength C_s. Under the same parameters (e.g. C_s and the dissipation rates), we find that the separation of the quantum state in the WFs representation is different from one system to another. Furthermore, since understanding these kinds of systems is very important in order to improve the quantum network system, we study the entropy S of the subsystems (such as S of qubit) in each system. Also, we move beyond by studying the effect of the temperature on the Fock-state distribution occupation probability and entropy of the subsystems. Our results present another step to understanding the qubit(s)-cavity interaction to improve the performance of future quantum networks based on this system. Where the interplay between temperature, coupling strengths, and the Fock-state occupation probabilities contributes significantly to the understandi

关键词： Cavity Dicke model Quantum communication networks Quantum nodes Quantum state Qubit Qubit–cavity system Temperature

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Integrating Ontology-Based Approaches with Deep Learning Models for Fine-Grained Sentiment Analysis

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computers, Materials & Continua 2024年第10期81卷 1855-1877页

作者： Longgang Zhao Seok-Won Lee The Knowledge-Intensive Software Engineering(NiSE)Research Group Department of Artificial IntelligenceAjou UniversitySuwon City16499Republic of Korea Department of Software and Computer Engineering Ajou UniversitySuwon City16499Republic of Korea

Although sentiment analysis is pivotal to understanding user preferences,existing models face significant challenges in handling context-dependent sentiments,sarcasm,and nuanced *** study addresses these challenges by integrating ontology-based methods with deep learning models,thereby enhancing sentiment analysis accuracy in complex domains such as film reviews and restaurant *** framework comprises explicit topic recognition,followed by implicit topic identification to mitigate topic interference in subsequent sentiment *** the context of sentiment analysis,we develop an expanded sentiment lexicon based on domainspecific corpora by leveraging techniques such as word-frequency analysis and word ***,we introduce a sentiment recognition method based on both ontology-derived sentiment features and sentiment *** evaluate the performance of our system using a dataset of 10,500 restaurant reviews,focusing on sentiment classification *** incorporation of specialized lexicons and ontology structures enables the framework to discern subtle sentiment variations and context-specific expressions,thereby improving the overall sentiment-analysis *** results demonstrate that the integration of ontology-based methods and deep learning models significantly improves sentiment analysis accuracy.

关键词： Deep learning ontology fine-grained sentiment analysis online reviews

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Towards a formal model to reason about context-aware exception handling

Towards a formal model to reason about context-aware excepti...

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2012 5th International Workshop on Exception Handling, WEH 2012

作者： Rocha, Lincoln S. Andrade, Rossana M. C. Group of Computer Networks Software Engineering and Systems Graduate Program in Computer Science Federal University of Ceará Fortaleza - CE Brazil

ISBN: (纸本)9781467317665

The context-awareness is a central aspect in the design of pervasive systems, characterizing their ability to adapt its structure and behavior. The context-aware exception handling (CAEH) is an existing approach employed to design exception handling in pervasive systems. In this approach, the context is used to define, detect, propagate, and handle exceptions. CAEH is a complex and error prone activity, needing designers' insights and domain expertise to identify and characterize contextual exceptions. However, despite the existence of formal methods to analyze the adaptive behavior of pervasive systems, such methods lack specific support to specify the CAEH behavior. In this paper, we propose a formal model to reason about the CAEH behavior. It comprises an extension of the Kripke Structure to model the context evolution of a pervasive system and a transformation function that derivates the CAEH control flow from that proposed structure. © 2012 IEEE.

关键词： Model checking

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