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Building operator-centric digital twins for optical transport networks: from data models to real applications

JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING 2025年第6期17卷 B1-B14页

作者： Cherini, Renato Gonzalez-Montoro, Nehuen Gonzalez-Montoro, Aldana Compagnucci, Luis Finochietto, Jorge M. Univ Nacl Cordoba Ave Velez Sarsfield 1611 RA-5000 Cordoba Argentina Ceragon Networks 3801 E Plano Pkwy Plano TX 75074 USA Consejo Nacl Invest Cient & Tecn Ave Velez Sarsfield 1611 RA-5000 Cordoba Argentina

The complexity and heterogeneity of modern optical transport networks (OTNs) demand advanced solutions to enhance their operation and maintenance. This paper presents lessons learned from the design and implementation of a digital twin network (DTN) tailored to network operators' requirements, integrating hybrid models that combine physical representations with data-driven analysis. By leveraging telemetry data, the DTN can facilitate network operators to perform predictive maintenance, resource optimization, and risk analysis. Through a case study on soft failure detection across 454 optical sections, we analyze the value of transforming theoretical concepts coupled with collected data into actionable insights, reducing operational overhead and enhancing network resilience. This work underscores the potential of hybrid modeling in the context of DTN to create operator-centric solutions for optical transport networks.

关键词： Optical fiber networks data models Optical fibers Real-time systems Digital twins Complexity theory Adaptive optics Maintenance Adaptation models Physical layer

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Assessing ECG Interpretation Expertise in Medical Practitioners Through Eye Movement data and Neuromorphic models

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IEEE ACCESS 2025年 13卷 9430-9449页

作者： Bokhari, Syed Mohsin Shafi, Muhammad Noor, Fazal Sohaib, Sarmad Alqahtany, Saad Donnelly, Mark Univ Engn & Technol UET Taxila Dept Elect & Comp Engn Taxila 47050 Pakistan Ulster Univ Sch Comp BELFAST BT15 1ED North Ireland Sohar Univ Fac Comp & Informat Technol Sohar 311 Oman Islamic Univ Madinah FCIS Madinah 42351 Saudi Arabia Univ Jeddah Dept Elect & Elect Engn Jeddah 23218 Saudi Arabia

This study introduces an innovative method for assessing ECG interpretation abilities in medical professionals via eye-tracking data. We examine eye movement patterns from five separate groups of cardiology practitioners utilizing a combination of neuromorphic computing models, including Spiking Neural Networks (SNN), Spiking Convolutional Neural Networks (SCNN), Recurrent Spiking Neural Networks (RSNN), and Spiking Convolutional Long Short-Term Memory (SCLSTM). Utilizing eye movement data, we analyze the skill levels of practitioners in diverse medical positions, including consultants, nurses, and technicians, during ECG evaluations. Our proposed work combines spiking neuron activations with convolutional and recurrent architectures to analyze spatial and temporal gaze patterns that reflect clinical expertise. The suggested SNN, SCNN, RSNN, and SCLSTM models attained accuracies of 84.35%, 93.04%, 94.68%, 99.76% respectively, exceeding standard machine learning approaches in both precision and recall for identifying expertise levels based on visual attention patterns. This paradigm has the potential to construct skill evaluation tools in medical education, specifically for ECG interpretation training, thereby addressing prevalent difficulties related to inconsistent ECG diagnosis methods.

关键词： Electrocardiography Visualization Long short term memory Medical diagnostic imaging Cardiology Spiking neural networks data models Training Gaze tracking Biomedical imaging Spiking neural networks (SNN) spiking convolutional neural networks (SCNN) recurrent spiking neural networks (RSNN) spiking convolutional long short-term memory (SCLSTM) random forest ECG

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data Fusion and models Integration for Enhanced Semantic Segmentation in Remote Sensing

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2025年 18卷 7134-7151页

作者： Dong, Xiaorui Li, Jiansheng Chang, Qingfang Miao, Shufeng Wan, Hongxiang Informat Engn Univ Inst Geospatial Informat Zhengzhou 450001 Peoples R China Shandong Inst Petr & Chem Technol Sch Big Data & Basic Sci Dongying 257000 Peoples R China Wuhan Kedao Geog Informat Engn Co Ltd Wuhan 430081 Peoples R China

Remote sensing semantic segmentation is a key research area in the remote sensing domain. Despite advancements, there is still no unified standard dataset such as ImageNet for remote sensing segmentation. This fragmentation leads to scattered efforts, with different teams using various datasets, making horizontal comparisons and result sharing difficult. To address this issue, we propose a novel data fusion method for remote sensing semantic segmentation, which integrates remote sensing data from different sources and segmentation results, providing support for the creation of a unified, large-scale semantic segmentation dataset suitable for deep learning. This method promotes standardized research in remote sensing segmentation and provides a reference benchmark for cross-comparison of different research outcomes. To demonstrate the feasibility of the proposed method, we have constructed a fused dataset named GGDS, which integrates Google Maps satellite imagery with GlobeLand30 semantic labels. In addition, we designed and implemented model integration techniques for the fused dataset, improved the segmentation_models_pytorch library, and developed the EffiTUnet model based on it, achieving outstanding experimental results. The methods and tools presented in this article offer substantial support and convenience for related research. Our results not only account for the diversity and complexity of different remote sensing data but also enhance model generalization in various application scenarios through ensemble learning strategies, providing strong support for training more powerful and efficient semantic segmentation models.

关键词： Remote sensing Semantic segmentation data models Training Benchmark testing Deep learning data integration Semantics data mining Biological system modeling data fusion dataset preparation deep learning EffiTUnet models integration remote sensing semantic segmentation

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data models, representation and adequacy-for-purpose

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EUROPEAN JOURNAL FOR PHILOSOPHY OF SCIENCE 2021年第1期11卷 31页

作者： Bokulich, Alisa Parker, Wendy Boston Univ Dept Philosophy 745 Commonwealth AveRoom 516 Boston MA 02215 USA Virginia Tech Dept Philosophy 229 Major Williams Hall 0126 Blacksburg VA 24060 USA

We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational (PR) view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides insight into the common but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets' having a phylogeny-an origin and complex evolutionary history-that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data.

关键词： data data models data processing Scientific models Fit-for-purpose Legacy data Climate science Astrophysics Geosciences Pragmatism

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data models for information sharing in E-partnerships: Analysis, improvements, and relevance

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JOURNAL OF ORGANIZATIONAL COMPUTING AND ELECTRONIC COMMERCE 2002年第2期12卷 175-195页

作者： Jukic, B Jukic, N Parameswaran, M George Mason Univ Sch Management Fairfax VA 22030 USA Loyola Univ Dept Informat Syst & Operat Management Chicago IL 60611 USA Univ Maryland Dept Decis & Informat Technol Robert H Smith Sch Business College Pk MD 20742 USA

In this article we address the issue of sharing information in organizational forms involving parties with various levels of mutual trust and need for cooperation. We evaluate existing data access models and emphasize their failure to deliver a feasible method for providing consistent views of corporate information shared with other partners in an ad hoc relationship. A new data access model is proposed as a solution to this problem. This model combines the ease of maintenance with the ability to present semantically consistent views of the world to all constituents of a virtual enterprise. We discuss the relevance of information sharing across multiple-access levels for achieving competitive advantage in the electronic marketplace.

关键词： data models access control business-to-business e-commerce virtual enterprises semantics relational databases

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COMPARISON OF SOME data models FOR ENGINEERING OBJECTS

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IEEE COMPUTER GRAPHICS AND APPLICATIONS 1987年第3期7卷 56-66页

作者： HARDWICK, M SPOONER, DL RENSSELAER POLYTECH INST DEPT COMP SCITROYNY 12181

Many proposals using object-oriented data models for engineering objects have appeared in the literature. These data models try to represent the data in engineering systems more naturally by organizing it logically and/or physically into objects relevant to the engineering applications using the database. In this article we review and examine several of these proposed data models to identif important properties of the models. We show that none of the data models excels in all areas, but each has desirable properties.

关键词： data models data engineering Object oriented modeling Relational databases database systems Systems engineering and theory Application software Integrated circuit modeling

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Logical data models for Cloud Computing Architectures

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IT PROFESSIONAL 2012年第1期14卷 19-26页

作者： Samba, Augustine (Gus) Kent State Univ Coll Technol Kent OH 44242 USA Kent State Univ Sch Digital Sci Kent OH 44242 USA

Describing generic logical data models for two existing cloud computing architectures, the author helps develop a common set of architectural requirements to facilitate traceability between evolving business requireme... 详细信息

关键词： Cloud computing logical data models multitenancy ARCHITECTURE traceability Cloud Computing data models logical

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Applying data models to big data architectures

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IBM JOURNAL OF RESEARCH AND DEVELOPMENT 2014年第5-6期58卷 18:1-18:11页

作者： O'Sullivan, P. Thompson, G. Clifford, A. IBM Software Grp Dublin 15 Ireland

A key message from the early adopters of big data is that technologies such as Hadoop (R), NoSQL (Not Only Structured Query Language) databases, and stream computing should not be seen as completely separate technologies but are more valuable when deployed in conjunction with more traditional data management components. There is an urgent need for an overall blueprint for treating both the new and traditional data management components in a holistic and integrated manner. A models-driven approach ensures consistency across this data management landscape in terms of management, governance, and efficiency. This paper focuses on the data modeling considerations relating the big data deployment using the examples of transaction data and mixed unstructured data to ensure that data components are evolved to maximize business value and development efficiencies.

关键词： Big data Business data models database management Transaction processsing

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Geoscience explanations: Identifying what is needed for generating scientific narratives from data models

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ENVIRONMENTAL MODELLING & SOFTWARE 2010年第1期25卷 93-99页

作者： Reitsma, Femke Univ Canterbury Christchurch 1 New Zealand

As models of geoscience systems grow in number and size, so grows the need for tools to help express the output of those models in usable forms. In this paper the utility of the output of a model is defined as its ability to support scientific explanation. Commonly the output of a model might include statistics, graphs, maps, images and animations, which require expert interpretation and evaluation in the context of the model setup or implementation. Here the narrative is presented as a type of output from a model that can present the results of a model in a form that is more useful for the non-expert. Narratives provide a rich medium for expressing causal chains of events that form the basis for explanation and its future use in policy and decision making. This paper reviews research on narratives and their role in scientific explanation. The principles of narrative construction for the Geosciences are identified, which forms the basis for determining the key components needed in explanatory statements for communicating the output of geoscience models. The potential of existing data models used in model output for generating narratives are explored, followed by the conceptual presentation of an extended data model, which supports the narrative unit and has the potential to automate aspects of the generation of scientific explanation in narrative form. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： data models Scientific narrative Scientific explanation

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Optimizing the Execution of Product data models

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IEEE ACCESS 2024年 12卷 25397-25410页

作者： Varvoutas, Konstantinos Bellas, Christos Kougka, Georgia Gounaris, Anastasios Aristotle Univ Thessaloniki Dept Informat Thessaloniki 54124 Greece

The Product data Model (PDM) is an example of a declarative data-centric approach to modelling information-intensive business processes, which offers flexibility and facilitates process optimization. Declarative approaches are the de facto choice in all modern data-oriented workflows, but they require an optimizer to choose among multiple, alternative execution plans that can produce the desired end product. In PDM business processes, current optimization heuristics suffer from severe limitations regarding both their efficiency and applicability to realistic scenarios, stemming from a lack of consideration for the resource perspective of the processes being modelled and the advances in modern data flow optimizers. This work tackles both of these limitations with the proposal of rank-based operation ordering optimizations tailored to the specificities of PDM, which are also combined with the consideration of the resources available to execute the process operations and parallelism options. Through an extensive evaluation of the proposed solutions, it is showcased that there are significant performance gains from the advanced rank-based operation ordering techniques with the added support of parallel execution. The speedups observed were up to 5.5X compared to the state-of-the-art optimization heuristics.

关键词： Optimization methods data models Business Task analysis Computational modeling Proposals Product development Performance gain Resource management Heuristic algorithms Business process management data-centric processes PDM process optimization

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