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检索条件"丛书名=Communications in Computer and Information Science"

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Generative Style Transfer for MR Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan Africa 1st

Generative Style Transfer for MR Image Segmentation: A Case ...

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1st MICCAI Meets Africa Workshop

作者： Chepchirchir, Rancy Sunday, Jill Confidence, Raymond Zhang, Dong Chaudhry, Talha Anazodo, Udunna C. Muchungi, Kendi Zou, Yujing Strathmore Univ Inst Math Sci Nairobi Kenya Univ Hull Fac Sci & Engn Kingston Upon Hull England Tech Univ Mombasa Dept Med Engn Mombasa Kenya Med Artificial Intelligence Lab Lagos Nigeria Lawson Hlth Res Inst London ON Canada Univ British Columbia Dept Elect & Comp Engn Vancouver BC Canada Univ Nairobi Nairobi Kenya Univ Cape Town Dept Clin & Radiat Oncol Cape Town South Africa McGill Univ Montreal Neurol Inst Montreal PQ Canada Aga Khan Univ Brain Mind Inst Nairobi Kenya McGill Univ Med Phys Unit Montreal PQ Canada

ISBN: (纸本)9783031791024;9783031791031

In Sub-Saharan Africa (SSA), the utilization of lower-quality Magnetic Resonance Imaging (MRI) technology raises questions about the applicability of machine learning (ML) methods for clinical tasks. This study aims to provide a robust deep learning-based brain tumor segmentation (BraTS) method tailored for the SSA population using a threefold approach. Firstly, the impact of domain shift from the SSA training data on model efficacy was examined, revealing no significant ***, a comparative analysis of 3D and 2D full-resolution models using the nnU-Net framework indicates similar performance of both the models trained for 300 epochs achieving a five-fold cross-validation score of 0.93. Lastly, addressing the performance gap observed in SSA validation as opposed to the relatively larger BraTS glioma (GLI) validation set, two strategies are proposed: fine-tuning SSA cases using the GLI + SSA best-pretrained 2D fullres model at 300 epochs, and introducing a novel neural style transfer-based data augmentation technique for the SSA cases. This investigation underscores the potential of enhancing brain tumor prediction within SSA's unique healthcare landscape.

关键词： Brain Tumor Segmentation Neural style transfer nnU-Net

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Research on Seafood Traceability System Based on Blockchain 5th

Research on Seafood Traceability System Based on Blockchain

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5th China Intelligent Robotics Academic Conference

作者： Liu, Chang Li, Chang Ling, Yurou Ling, Yuan Na, Zhenyu Dalian Maritime Univ Dalian Liaoning Peoples R China Normal Univ High Sch Liaoning Dalian Liaoning Peoples R China Zhida Informat Technol Co Ltd Dalian Liaoning Peoples R China

ISBN: (纸本)9789819616138;9789819616145

The traditional traceability field suffers from shortcomings such as opaque product circulation and centralized management. Owing to its decentralized, tamper-proof, and easy-to-trace characteristics, blockchain has gradually emerged as the preferred choice for traceability. This paper introduces the blockchain data structure and smart contract, and then proposes a seafood traceability system grounded in blockchain after a thorough analysis of the challenges in traditional seafood traceability. The system employs hyperledger fabric as its underlying framework, which is combined with the InterPlanetary File System's (IPFS) permanent and decentralized storage, alleviating the high storage costs and low efficiency issues caused by excessive data. The feasibility of this scheme is confirmed through performance testing of the system.

关键词： Seafood traceability Blockchain Smart contract Data sharing

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Verification-Oriented Specification of Multi-agent Interaction Patterns 4th

Verification-Oriented Specification of Multi-agent Interacti...

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4th Workshops on Agents and Robots for Reliable Engineered Autonomy

作者： Tagliaferro, Alberto Lestingi, Livia Rossi, Matteo Politecn Milan Milan Italy

ISBN: (纸本)9783031731792;9783031731808

Smart cyber agents are pivotal in software-intensive systems such as smart manufacturing, robotics, and the Internet of Things. These agents monitor physical surroundings through sensors and make impactful decisions that influence the environment. Software engineering challenges in this domain include the specification of interactive multi-agent tasks. The general-purpose Domain-Specific Language named LIrAs, Language for Interactive Agents, is a high-level language that allows for unambiguous custom pattern definition. Additionally, LIrAs facilitates interactions with human agents, a safety-critical situation requiring particular attention. This paper lays the foundation for LIrAs specifications translation to Stochastic Hybrid Automaton (SHA). The target SHA model structure follows a three-layer hierarchical structure and makes LIrAs specifications amenable to formal verification, specifically Statistical Model Checking, through the Uppaal tool, capable of including time-dependent physical phenomena, such as human fatigue and robot dynamics.

关键词： Multi-Agent Patterns Specification Domain-Specific Language Stochastic Hybrid Automata

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Generalized Possibilistic CTL* Model Checking with Fuzzy Temporal Logic Operators 42nd

Generalized Possibilistic CTL* Model Checking with Fuzzy Tem...

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42nd National Conference on Theoretical computer science

作者： Mu, Chuanjiang Liu, Wuniu Li, Yongming Shaanxi Normal Univ Sch Comp Sci Xian Shaanxi Peoples R China Shaanxi Normal Univ Sch Math & Stat Xian Shaanxi Peoples R China

ISBN: (纸本)9789819614899;9789819614905

Based on the generalized possibilistic Kripke structure, possibilistic fuzzy linear temporal logic, GPoCTL* and generalized possibility measure, this article studies the model-checking problems of generalized possibilistic fuzzy CTL* (GPoFCTL*). GPoFCTL* includes fuzzy temporal logic operators such as "soon", "presently", "gradually", "last", "within","finally", "nearly always", "almost always", "in the distant future", "in the middle", "almost until", "nearly until". This paper studies the syntax of GPoFCTL* and its semantics based on generalized possibility measures. In addition, we present an model checking algorithm for GPoFCTL* using fuzzy matrix operations. Finally, we present an example to illustrate the computational process of the model checking algorithm.

关键词： Generalized possibility theory fuzzy temporal operator GPoFCTL model checking

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EEG Biometrics with GAN Integration for Secure Smart City Data Access 1

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8th International Conference on computer-Human Interaction Research and Applications-CHIRA-Annual

作者： Saia, Roberto Balia, Riccardo Podda, Alessandro Sebastian Pompianu, Livio Carta, Salvatore Pisu, Alessia Univ Cagliari Dept Math & Comp Sci Palazzo SciVia Osped 72 I-09124 Cagliari Italy

ISBN: (数字)9783031826337

ISBN: (纸本)9783031826320;9783031826337

Biometric systems leveraging ElectroEncephaloGram (EEG) data for user authentication present significant potential in diverse contexts, especially in Smart City ecosystems where secure access to sensitive data is crucial (e.g., healthcare systems, intelligent transportation, smart grids, public safety, and citizen services). However, the complexity and variability of EEG data raise challenges in developing effective solutions. In this context, after a preliminary series of experiments used to find the best feature extraction method for the input, and performed by exploiting the Biometric EEG Dataset (BED), this paper proposes a novel EEG-based user verification framework. It utilizes Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction, followed by feature selection via the Boruta strategy and automated data quantization. An important aspect of this approach is the integration of Generative Adversarial Networks (GANs) to generate synthetic EEG data, which, along with real data, is employed to train an ensemble of Artificial Neural Networks (ANNs). The ensemble decision is made using soft voting mechanisms, promising a robust and competitive solution compared to current state-of-the-art techniques. Initial experiments suggest that this framework has significant potential for further development and optimization.

关键词： Smart cities Brain-computer interfaces Biometrics EEG data Secure access

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AI Ethics in Practice: Exploring Racial and Ethnic Stereotypes in Synthetic Resumes Written by ChatGPT 4th

AI Ethics in Practice: Exploring Racial and Ethnic Stereotyp...

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4th International Conference on Artificial Intelligence and Knowledge Processing

作者： Benzel, Jessica Rege, Manjeet Univ St Thomas Dept Software Engn & Data Sci St Paul MN 55105 USA

ISBN: (纸本)9783031734762;9783031734779

Generative artificial intelligence (AI) and large language models (LLM) are gaining focus in a number of industries, including the field of human resources (HR), and are attracting new attention with the release of OpenAI's ChatGPT in late 2022. This study focuses on generative AI output in the context of ethical AI and algorithmic hiring practices by exploring differences in ChatGPT's responses to resume writing prompts for multiple race/ethnicity categories, using a variety of methods to identify and evaluate those differences and assess bias. We find that there are observable qualitative differences in some of the output produced by ChatGPT in response to prompts for different races and ethnicities. These differences reflect potentially harmful bias and may promote racial, ethnic, and cultural stereotypes. As such, it is critical for data scientists and HR practitioners to use a variety of methods to rigorously assess the presence of bias and the potential for harm when considering the use of synthetic data in algorithmic hiring practices and other applications. This study addresses ethical concerns regarding the use of ChatGPT to create synthetic text data to train other AI models due to its potential to perpetuate racial and ethnic bias.

关键词： AI Ethics Generative AI Applications Digital Humanities

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Holistic Ontology Alignment Using Ontologies Embeddings 4th

Holistic Ontology Alignment Using Ontologies Embeddings

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4th International Conference on Intelligent Systems and Pattern Recognition-ISPR

作者： Akremi, Houda Zghal, Sami Univ Jendouba Inst Natl Technol & Sci Kef Le Kef 7100 Tunisia Univ Tunis El Manar Fac Sci Tunis Tunis 2092 Tunisia Univ Jendouba Fac Sci Jurid Econ & Gest Jendouba Jendouba 8189 Tunisia

ISBN: (纸本)9783031821554;9783031821561

In the realm of Semantic Web, aligning ontologies holistically presents a formidable challenge for effective knowledge integration. Traditional approaches to ontology matching often fall short of capturing comprehensive semantic relationships across multiple ontologies simultaneously. The Holistic Matching paradigm aims to address this challenge by considering the entirety of ontological structures, facilitating a more nuanced understanding of semantic interconnections and relationships. However, achieving holistic alignment poses its own set of challenges, including semantic heterogeneity, evolving ontologies, and scalability issues. In response to these challenges, this paper explores the integration of ontology embedding techniques within the holistic matching framework. Ontology embedding offers a promising avenue to capture nuanced semantic associations and contextually-sensitive relationships by representing ontological entities in a continuous vector space. In this study, we introduce a holistic ontology alignment using ontologies Embeddings. We examine the ontologies Embeddings for measuring similarity between ontologies, and discovering holistic ontology alignment between elements. Our experiments with the Ontology Alignment Evaluation Initiative (OAEI) achieved competitive results compared to the leading systems.

关键词： Ontology Ontology Embedding Similarity Holistic Matching

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Fogg Behavioural Model Based Cybersecurity Awareness Framework: An Empirical Analysis 15th

Fogg Behavioural Model Based Cybersecurity Awareness Framewo...

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15th Indian Conference on Human-computer Interaction Design and Research

作者： Shah, Pintu R. SVKMs NMIMS Mukesh Patel Sch Technol Management & Mumbai Maharashtra India

ISBN: (纸本)9783031808289;9783031808296

Cyber threats have emerged as one of the significant risks facing governments, organizations and individuals. The sophistication and frequency of cyber-attacks are increasing daily despite advanced security controls. This trend indicates the need to look beyond technical security controls to prevent cyber incidents. The previous research suggests that security education, training, and awareness (SETA) programs are effective countermeasures along with other technical and administrative controls. The end user's security behaviour is critical in mitigating cyber threats. However, prior research studies indicate that most SETA programs fail to meet their objectives for various reasons. One of the reasons is the lack of systematic and theory-based design and development process of the SETA program. This paper proposes a framework for enhancing the cybersecurity behaviours of smartphone users based on the Fogg Behavioural Model (FBM). The FBM is used to design a power prompt in the proposed framework. The proposed framework was tested using a between-subjects design (n = 94) and found to be effective in creating cybersecurity awareness. The participants in the intervention group are 2.65 times more likely to adopt recommended behaviours. This framework may be useful in the design of an effective SETA program.

关键词： Fogg Behavioural Model Smartphone User User Behaviour Cybersecurity Framework SETA Program

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FGPE - An Evolving Framework for Gamified Programming Learning

FGPE - An Evolving Framework for Gamified Programming Learni...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Queiros, Ricardo Swacha, Jakub Damasevicius, Robertas Maskeliunas, Rytis CRACS INESC TEC Porto Portugal Polytech Porto ESMAD Porto Portugal Univ Szczecin Szczecin Poland Kaunas Univ Technol Kaunas Lithuania

ISBN: (纸本)9783031834349;9783031834356

This paper presents an overview of the FGPE (Framework for Gamified Programming Education), a set of three Erasmus+ projects aimed at providing a framework for applying gamification to programming education. The overview will encompass all three phases of the framework development, emphasizing the gamification elements embedded in the design and implementation of the outputs of each phase. These outputs will be presented as a unified narrative, including the gamification framework for programming exercises, a format for defining gamification details for programming exercises and courses, the authoring tool for the gamification layer, a gamification Web service, a tutorial on gamifying programming exercises (guidance material), and a tool that automatically generates gamified programming exercises.

关键词： computer Programming Gamification Automatic Assessment

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Real-Time Anomaly Detection Algorithm for DoS Attacks in Communication Networks with IEDs Using IEC 61850

Real-Time Anomaly Detection Algorithm for DoS Attacks in Com...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Castillo, Tomas Soto, Ismael Chavez, Hector Univ Santiago Chile Estacion Cent Chile

ISBN: (纸本)9783031834318;9783031834325

This paper tackles the cybersecurity challenges in smart energy systems using the IEC 61850 standard. We propose a real-time anomaly detection algorithm for identifying Denial of Service (DoS) attacks in networks with Intelligent Electronic Devices (IEDs). The algorithm, based on an Autoencoder neural network, analyzes network traffic to detect anomalies via reconstruction errors. Tested on a dataset with both normal and DoS attack traffic, the algorithm achieved optimal results, with the 90th percentile showing the highest F1-Score and perfect Recall, ensuring no anomalies are missed. The findings highlight its effectiveness in enhancing the cybersecurity of smart energy networks.

关键词： Cybersecurity DoS IEC 61850 Anomaly Detection Machine Learning Energy Networks Real-time IED

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