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

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An Ontology Framework for Human-Robot Interoperability in Dynamic Construction Environments 5th

An Ontology Framework for Human-Robot Interoperability in Dy...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Karapanagiotis, Pantelis Koester, Felix Emmanouilidis, Christos Univ Groningen Nettelbosje 2 NL-9747 AE Groningen Netherlands

ISBN: (纸本)9783031807749;9783031807756

Humans and robots increasingly work collaboratively in work environments. Their synergy varies between simple co-existence, wherein they perform independently in shared spaces, to deep collaboration, wherein the joint outcome of their co-working cannot be attributed to either one of the two types of actors alone. Relevant concepts are that of human agency, when robots operate under human oversight, with humans assuming control in appropriate circumstances, and sliding autonomy, where control slides back and forth between humans and robots, depending on the situational context. This study introduces an ontology framework for human-robot interoperability (HRI) in dynamic construction environments. The ontology serves as a context model, facilitating task allocation and collaboration between humans and robots under a Construction Sliding Work Sharing (CSWS) scheme. While previous ontology designs focused either on aspects of construction processes or human-robot collaboration, the ontological formalization of the intersection of HRI and dynamic construction environments is unexplored. The CSWS ontology integrates human-centricity, dynamic task distribution, and human-robot interoperability concepts in construction settings. The ontology development process combines concepts distilled from qualitative content analysis of a construction case study with relevant concepts from previous literature and ontologies. The ontology is consistent with the Sliding Work Sharing (SWS) concept, an extension of sliding autonomy for dynamic task allocation across human and robot actors. The capacity of the CSWS ontology to support dynamic task allocation and human-robot collaboration is exemplified via use cases querying for agent safety, process errors, and human-robot collaborative activities.

关键词： Cobots Construction robotics Human-centricity Human-robot interoperability Ontology Sliding autonomy Sliding work sharing

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Enhancing SHI Extraction and Time Normalization in Healthcare Records Using LLMs and Dual-Model Voting

Enhancing SHI Extraction and Time Normalization in Healthcar...

引用

2024 International Workshop on Deidentification of Electronic Medical Record Notes

作者： Huang, PeiWen Liu, Tzu-En Natl Taiwan Univ 1 Sec 4 Roosevelt Rd Taipei 10617 Taiwan

ISBN: (纸本)9789819779659;9789819779666

Our study evaluates the effectiveness of discriminative and generative models in protecting privacy and standardizing medical data, focusing on Sensitive Health information (SHI) extraction and Time information Normalization (TIN) in medical records. Utilizing advanced pre-trained models, we introduce a dual-model fusion with a voting mechanism, diverse data forms, and data augmentation techniques. Our experiments demonstrate the superiority of generative models over traditional discriminative models in the SHI extraction task. This paper underscores the significance of strategic model selection, adept data processing, and the novel voting mechanism in enhancing the performance of SHI extraction and TIN tasks. Our methods achieve remarkable performance both on SHI extraction and TIN tasks. These results pave the way for advanced AI applications in healthcare, offering valuable insights for ongoing research in medical data management and privacy safeguarding.

关键词： Generative Models Name Entity Recognition Voting Mechanism Sensitive Health information Extraction Time information Normalization

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Integrating eXplainable AI in Healthcare: A Web Application Framework for Advancing the One Health Paradigm 4th

Integrating eXplainable AI in Healthcare: A Web Application ...

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24th International Conference Web Engineering (ICWE)

作者： Danese, Danilo Di Noia, Tommaso Lombardi, Angela Lofu, Domenico Nazary, Fatemeh Sardone, Rodolfo Sorino, Paolo Politecn Bari Dept Elect & Informat Engn DEI Bari Italy Univ Liverpool Inst Life Course & Med Sci Liverpool Merseyside England

ISBN: (纸本)9783031751097;9783031751103

In today's complex world, the intricate connections between human health, socio-economic factors, and environmental conditions necessitate a holistic approach to health challenges. This paper highlights the critical need for the One Health paradigm, emphasizing a comprehensive framework that integrates human, economic, and environmental health considerations. By incorporating Explainable Artificial Intelligence (XAI) principles, this paper showcases a pioneering method to make the sophisticated insights derived from AI more accessible and actionable for a broad range of stakeholders, including healthcare professionals, environmental experts, and policy makers. Within the framework of the MISTRAL H2020 European project, we illustrate a healthcare model that employs XAI to demystify AI algorithms, thereby fostering trust and enhancing understanding among its users. This innovative approach not only improves clinical decision-making but also addresses environmental health issues by rendering the opaque decision-making processes ofMachine Learning (ML) models transparent and understandable. The framework's significance is underlined by its capacity to inform Health Impact Assessments (HIA) and predict disease risks, facilitating precise interventions and informed policy development. Furthermore, we propose a method for engineering and accessing this framework online, allowing users to engage directly with the system.

关键词： Explainable Artificial Intelligence Web Application Life science

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UKRAG: A Unified Knowledge Graph to Enhance Retrieval Augmented Generation Performance 5th

UKRAG: A Unified Knowledge Graph to Enhance Retrieval Augmen...

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5th International Symposium on Intelligent Computing Systems

作者： Alkouz, Akram Al-Saleh, Mohammed I. Alarabeyyat, Abdulsalam Bouchahma, Majed Higher Colleges Technol Comp Informat Syst Abu Dhabi U Arab Emirates Jordan Univ Sci & Technol Comp Sci Dept Irbid Jordan Balqa Appl Univ Software Engn Dept Salt Jordan

ISBN: (纸本)9783031829307;9783031829314

Retrieval Augmented Generation models have demonstrated significant potential in enhancing the performance and reducing hallucinations in Large Language Models by incorporating external knowledge sources. However, effectively utilizing both structured and unstructured data in Retrieval-Augmented Generation remains a challenge, as most existing methods retrieve only short, contiguous chunks from a retrieval corpus, limiting the holistic understanding of the overall document context and structure. This paper presents a novel approach to constructing a knowledge graph that seamlessly integrates structured and unstructured data to enhance the performance of Retrieval-Augmented Generation models. Our method involves first converting structured data into a graph model and then merging it with the document context found in unstructured text. This combined data is processed to build a Unified Knowledge graph, providing a rich, interconnected information source for the Retrieval-Augmented Generation model. To evaluate our approach and proposed model, we conducted extensive experiments on a variety of tasks, including question-answering and complex reasoning. The results demonstrate that our Unified knowledge Graph RAG model significantly outperforms traditional RAG models, achieving higher accuracy and better handling of intricate queries. Notably, on benchmarks such as QuALITY, our model shows substantial improvements in performance metrics. This research underscores the potential of integrating structured and unstructured data into a unified knowledge graph to advance the capabilities of RAG models, offering a promising direction for future developments in Artificial Intelligence and Natural Language Processing.

关键词： Knowledge graph

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LANet: Lightweight Attention Network for Medical Image Segmentation 2nd

LANet: Lightweight Attention Network for Medical Image Segme...

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2nd International Conference on information Technologies and Their Applications

作者： Tang, Yi Pertsau, Dmitry Zhao, Di Kupryianava, Dziana Tatur, Mikhail Belarusian State Univ Informat & Radioelect Minsk BELARUS

ISBN: (纸本)9783031734199;9783031734205

Medical image segmentation plays a crucial role in quantitative analysis, clinical diagnosis and medical interventions. However, extracting valuable information from medical images is challenging due to the presence of different object types and scales, complex backgrounds and tissue similarities. To address these issues, LANet, a Lightweight Attention Network which incorporates an Efficient Fusion Attention (EFA) block and an Adaptive Feature Fusion (AFF) decoding block was presented in the paper. The EFA block enhances the model's feature extraction capability by capturing task-relevant information while reducing redundancy in channel and spatial locations. The AFF decoding block fuses the purified low-level features from the encoder with the sampled features from the decoder, enhancing the network's understanding and expression of input features. Additionally, the model adopts MobileViT as a lightweight backbone network with a small number of parameters, facilitating easy training and faster predictive inference. The efficiency of LANet was evaluated using four public datasets: kvasir-SEG, CVC-clinicDB, CVC-colonDB, and the Data science Bowl 2018. Experimental results demonstrate that LANet outperforms state-of-the-art methods in terms of intersection over union (mIoU) and Dice scores.

关键词： LANet Lightweight Attention Network Efficient Fusion Attention Block Adaptive Feature Fusion Decoding Block Attention Mechanism

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Integration of Social Design with ICT to Promote Sustainability 15th

Integration of Social Design with ICT to Promote Sustainabil...

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

作者： Sharma, Anubha Sharma, Divy Jain, Vikshita Aastha Agarwal, Kanan Agarwal, Kinshuk Absolom, Anisha Ajay Kumar Garg Engn Coll Ghaziabad Uttar Pradesh India Indian Inst Foreign Trade Kakinada India Indian Inst Technol Hyderabad Sangareddy Telangana India

ISBN: (纸本)9783031808319;9783031808326

This study will explore and combine information Communication Technology (ICT) with Social Design principles. The aim is to promote sustainable use of water through AquaAlert, a smart water management system. AquaAlert caters to monitoring real-time water usage, detecting water leakage, and providing actionable insights to users to reduce water consumption. A mixed-method approach was deployed during the research, using surveys, interviews, and tests to detect the effectiveness of the device and system. The findings revealed the true potential of AquaAlert, focusing on sustainability and promoting the United Nation's Sustainable Development Goals (SDGs) related to clean water and sustainable cities. The paper will include the user-centered design approach, development process, and research methodology implemented to promote responsible water usage.

关键词： Social Design information Communication Technology(ICT) Sustainable Development Goals Sustainability Behavioral Design

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Exploring the Effectiveness of a Multilingual Generative AI Programming Chatbot for Vernacular Medium CS Students 17th

Exploring the Effectiveness of a Multilingual Generative AI ...

引用

17th India Compute Conference-COMPUTE-Annual

作者： Halani, Avval Prasad, Prajish Sane, Aamod FLAME Univ Sch Comp & Data Sci Pune Maharashtra India

ISBN: (纸本)9783031843907;9783031843914

The integration of Generative Artificial Intelligence into education has the potential to revolutionize the way vernacular medium students engage with and learn complex subjects such as programming where most available material is in English. This exploratory study is the first step of the Sanganmitra project, where we investigate the effectiveness of a Generative AI-powered programming chatbot for Vernacular Medium with English Materials (VMEM) students. The chatbot was designed to assist students with programming challenges without providing direct solutions. Students were presented with 3 programming problems and could interact with the tool in either English or Marathi. We conducted a study with 42 VMEM students to understand how they interacted with the tool. We also explored if there are differences in the usage between students who use it in English or Marathi. Our findings show that 21% of students conversed with the chatbot in Marathi, a significant number considering the predominance of English in STEM. A slightly higher percentage of Marathi users asked conceptual or relevant questions. However, in general students merely asked for the full solution by repeating the question. We discuss some implications of these patterns for future studies.

关键词： LLM Generative AI Vernacular Education Chatbot CS Education Native Language Education NNES VMEM

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Cost-Effective Tension Testing System for Plastics Industries 4th

Cost-Effective Tension Testing System for Plastics Industrie...

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

作者： Guerra, Michael Abedrabbo, Faruk Moya, Viviana Quito, Angelica Mosquera, Guillermo Pablo Vasconez, Juan Univ Int Ecuador UIDE Fac Ciencias Tecn Quito 170411 Ecuador Univ Andres Bello Energy Transformat Ctr Fac Engn Santiago 7500971 Chile

ISBN: (纸本)9783031832062;9783031832079

To determine mechanical properties or other relevant parameters of plastic materials, devices such as tensile testing machines are widely used. However, these procedures are performed with relatively expensive equipment that is not easily available in educational institutions or companies. For this reason, the following work presents the development and validation of a cost-effective machine capable of performing tensile tests with uniaxial loads on plastic materials. The main characteristics regarding the mechanical, electronic, and software design that have been developed and implemented for the correct operation of the machine are briefly and clearly disclosed. Likewise, the calibration process was performed using a known spring elastic constant. Additionally, the application and validation of the machine were carried out by comparing tensile tests done on the plastic straps with tests done in another machine. The results obtained by the developed machine are similar to those estimated by the validation machine in terms of mass and strain, obtaining an average accuracy of 2.46% and 2.17%, respectively. Finally, the machine sale price was estimated at $1,908 USD, a reduction cost of 68.2% compared with other similar machines in the industry.

关键词： Tensile test cost-effective machine plastic materials mechatronics design

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An Out-of-Sample Clustering Ensemble Method for Defect Detection and Classification in Metal Additive Manufacturing 5th

An Out-of-Sample Clustering Ensemble Method for Defect Detec...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Chabanet, Sylvain Orta, Adil Han Kersemans, Mathias Univ Ghent Dept Mat Text & Chem Engn Mech Mat & Struct Technol Pk 46 B-9052 Zwijnaarde Belgium SIM STREAM Technol Pk 48 B-9052 Zwijnaarde Belgium

ISBN: (纸本)9783031807596;9783031807602

Unsupervised learning methods, and in particular clustering algorithms, have found many applications in manufacturing, ranging from customer segmentation to quality monitoring. It has, however, been demonstrated that no clustering algorithm can be suitable for all applications and data structures. Ensembles of clustering algorithms have emerged as a partial answer to this limitation, aiming at increasing the robustness of clustering algorithms by aggregating partitions discovered by many models. This robustness, however, comes at the cost of increased computational requirements to generate and aggregate partitions. The ability to quickly predict a cluster for new, out-of-sample data points without having to recompute the whole clustering algorithm from scratch is, therefore, a desirable property for many real-world applications. Such out-of-sample methods, however, are not straightforward in the context of clustering ensemble, and few models include one. As a step toward filling this gap, this article proposes a novel out-of-sample method for clustering ensemble algorithms following the median consensus framework. An application of this method is proposed for the detection and classification of defects in metal parts produced by additive manufacturing processes. The proposed method is compared with state-of-the-art algorithms on both artificial and experimental datasets, demonstrating its high performance and robustness.

关键词： Clustering ensemble Resonance testing Additive manufacturing Out-of-sample

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On Numerical Solution of Block-Structured Discrete Systems 2nd

On Numerical Solution of Block-Structured Discrete Systems

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2nd International Conference on information Technologies and Their Applications

作者： Asadova, Jamila Azerbaijan Univ Architecture & Construct Inst Control Syst Baku Azerbaijan

ISBN: (纸本)9783031734199;9783031734205

The paper presents a numerical methodology for solving high-dimensional discrete dynamical systems characterized by a block structure with boundary conditions that are non-separated between blocks. Direct application of classical methods of transferring boundary conditions is inefficient, since the block structure of the conditions, as for many other classes of problems, allows to speed up their solution considerably. In this approach the decomposition of complex processes into simpler sub-processes with known mathematical models is used, and the decomposition of a complex process is performed in such a way that the intermediate states of sub-processes do not affect each other, i.e. they are independent, and the connection between sub-processes is implemented only through their input and output states. In this case, as a rule, the conditions determining the links between sub-processes are characterized by poorly occupied Jacobi matrices. In the paper formulas that perform transferring of non-separated boundary conditions are presented and practical results demonstrating the efficacy of the proposed approach on a test problem are provided.

关键词： Discrete Dynamic Models Decomposition of Complex Objects Technique for Transferring Boundary Conditions Poorly Occupied Jacobi Matrices Discrete Systems with Concentrated or Distributed Parameters

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