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检索条件"任意字段=8th IEEE International Enterprise Distributed Object Computing Conference"

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Enabling scalable AI for Digital Health: interoperability, consent and ethics support 25

Enabling scalable AI for Digital Health: interoperability, c...

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25th ieee international enterprise distributed object computing conference (ieee EDOC)

作者： Milosevic, Zoran Best Practice Software Bundaberg Qld Australia

ISBN: (纸本)9781665444880

this paper proposes an approach for building scalable AI applications in digital health, with a specific focus on addressing interoperability, consent and ethics challenges. these challenges need to be considered in the context of increasingly available tooling for streamlined model development, training, validation, and deployment, while accommodating novel solutions for explainable AI support for clinicians. Such an approach is required because digital health ecosystems involve many data type created by different systems, and often used as part of workflows over different jurisdictional boundaries. Interoperability solutions are needed to support technical and business agreements between parties providing data and services, including knowledge intensive services, such as ML and AI. Computable expression of consent and ethics policies are needed to control how patient information is used, including compliance with regulative rules, possibly from different policy contexts. Our approach, based on the latest interoperability and enterprise policy standards may provide a useful guidance for the practitioners building scalable AI solutions for digital health.

关键词： interoperability digital health consent ethics deontic logic ODP enterprise language (ODP-EL) AI FHIR

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SiamDSA: Dual-Branch Self-Attention Siamese Network for Visual object Tracking 19

SiamDSA: Dual-Branch Self-Attention Siamese Network for Visu...

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2022 ieee SmartWorld, 19th ieee international conference on Ubiquitous Intelligence and computing, 2022 ieee international conference on Autonomous and Trusted Vehicles conference, 22nd ieee international conference on Scalable computing and Communications, 2022 ieee international conference on Digital Twin, 8th ieee international conference on Privacy computing and 2022 ieee international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Pei, Yang Xing, Weiwei Wei, Xiang Liu, Weibin Wang, Mingquan Sun, Fuyong Beijing Jiaotong University School of Software Engineering Beijing China Institute of Information Sceince Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350346558

In recent years, object tracking is studied and applied widely in human activity recognition. In object tracking scenarios, the object appearance changes significantly due to various factors, such as scale changes and deformation, which will drastically affect the robustness of the object tracking. To deal with the above issues, we propose a DSA module that integrates the siamese tracking network to implement the siamese network tracking methods based on the dual-branch self-attention (SiamDSA). It fuses object features of different scales to greatly enhance the target information and establish a better target appearance model for improving object tracking robustness. Specifically, a novel DSA module based on self-attention mechanism boosts the feature representation of objects from channel and spatial perspectives. And it is responsible for better focusing on the features of the target. We conduct experiments on GOT-IOK, OTB100 and VOT2018 datasets. the experimental results demonstrate that SiamDSA achieves superior performances and runs at 65 FPS, it further shows strong effectiveness and efficiency in object tracking. © 2022 ieee.

关键词： Computer vision

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enterprise Architecture Resilience by Design: A Method and Case Study Demonstration 25

Enterprise Architecture Resilience by Design: A Method and C...

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25th ieee international enterprise distributed object computing conference (ieee EDOC)

作者： Aldea, Adina Vaicekauskaite, Egle Daneva, Maya Piest, Jean Paul Sebastian Univ Twente Ind Engn & Business Informat Syst Enschede Netherlands Univ Twente Serv Cybersecur & Safety Enschede Netherlands

ISBN: (纸本)9781665444880

In the past decades, a broad range of technological innovations have helped organizations reach new levels of performance and have shaped the economies of the world and societies of the future. However, unexpected events, such as the COVID-19 pandemic and the blocking of the Suez Canal, have shown that many organizations are unprepared to deal with the impact of the disturbances that can occur. thus, organizations are challenged to include resilience in the design of their Information Systems and enterprise Architectures (EAs). We respond to this challange and propose a five-step method aimed to help organizations design resilient enterprise architectures to be able to better deal with (un-) expected disturbances. Our method builds upon the 'EA resilience by design' paradigm, combines knowledge from several domains, namely resilience, risk analysis, and EA, and leverages the ArchiMate 3.1 language to model several resilience characteristics. Using a case study at a leading manufacturing organization in the agri-food sector in Lithuania, we demonstrate the applicability of our method and draw some early lessons learned based on our very first evaluation with experts.

关键词： Resilience by design enterprise Architecture Resilience ArchiMate Risk management Industry 4.0 COVID-19 pandemic Society 5.0

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Egocentric Hand-object Interaction Detection 19

Egocentric Hand-object Interaction Detection

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作者： Lu, Yao Liu, Yanan University of Bristol Bristol United Kingdom Phillips Research Shanghai China Shanghai University School of Microelectronics Shanghai China University of Bristol Bristol Robotics Laboratory Bristol United Kingdom

ISBN: (纸本)9798350346558

In this paper, we propose a method to jointly determine the status of hand-object interaction. this is crucial for egocentric human activity understanding and interaction. From a computer vision perspective, we believe that determining whether a hand is interacting with an object depends on whether there is an interactive hand pose and whether the hand is touching the object. thus, we extract the hand pose, hand-object masks to jointly determine the interaction status. In order to solve the problem of hand pose estimation due to in-hand object occlusion, we use a multi-cam system to capture hand pose data from multiple perspectives. We evaluate and compare our method with the most recent work from Shan et al. [1] on selected images from EPIC-KITCHENS [2] dataset and achieve 89% accuracy on HOI (hand-object interaction) detection which is comparative to Shan's (92%). However, for real-time performance, our method can run over 30 FPS which is much more efficient than Shan's (1∼ 2 FPS). A demo can be found from https://***/watch?v=XVj3zBuynmQ. © 2022 ieee.

关键词： Computer vision

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Incorporating Trust into Collaborative Social computing Applications 25

Incorporating Trust into Collaborative Social Computing Appl...

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25th ieee international enterprise distributed object computing conference (ieee EDOC)

作者： Munoz, Paula Perez-Vereda, Alejandro Moreno, Nathalie Troya, Javier Vallecillo, Antonio Univ Malaga ITIS Software Malaga Spain Univ Castilla La Mancha Ciudad Real Spain

ISBN: (纸本)9781665435796

Mobile-based collaborative social computing applications represent an alternative to the server-centric models currently offered by major IT vendors, where users own the information they generate and take control over how other users access and exploit it. In this context, trust is fundamental for sharing information and making decisions based on the data collected from other users. this work develops a trust management system embedded in the Digital Avatars framework for collaborative social computing applications, using Subjective logic. It enables explicit representation and operation with trust information about both service providers (functional trust) and other users' opinions about these providers (referral trust) in peer-to-peer environments. the proposal is specified using high-level models that can also be simulated and validated, and serve as a guide for the corresponding implementations in an existing social computing application platform. the proposed solution has been successfully applied in a collaborative carpooling system, where users need to trust other users with whom they share travels.

关键词： collaborative social computing applications uncertainty trust

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Making Autonomous Stores Smarter (MASS): A Practical Solution to Improve Product Detection Performance Using Synthetic Dataset at Scale 8

Making Autonomous Stores Smarter (MASS): A Practical Solutio...

引用

8th ieee international conference on Smart Cloud, SmartCloud 2023

作者： Jin, Nanxin Shah, Devin Terven, Juan Lozada, Daniela Basurto Bennett, Zachary Chen, Long Yang, Baijian Purdue University West LafayetteIN United States AiFi Inc BurlingameCA United States

ISBN: (纸本)9798350313505

Product detection in large retail stores requires extensive annotated real data, which is expensive and lacks adaptability when new products are introduced. this paper presents an end-to-end product detection approach using domain randomization to generate large synthetic datasets for training. We propose a set of randomizations at the product and scene level and a method for generating large amounts of domain-randomized synthetic data. To evaluate performance on this dataset, we propose a pipeline where a model is pre-trained on simulation data and fine-tuned on small amounts of real data. To further close the domain gap, we use CycleGAN-based domain adaptation to generate photorealistic synthetic data for product classification. Our multi-class product detection solution achieves a 64% increase in mAP@0.5 when training on 20 times fewer real images, and our product classification solution achieves a 10.3% increase in Top-1 accuracy and a 4.92% increase in Top-5 accuracy when training on ten real samples per product. the results show that generating domain-randomized synthetic datasets is an accurate and scalable approach to product detection in stores and can aid autonomous store deployments by decreasing the labeling effort while increasing the accuracy of initial product classification. ©2023 ieee.

关键词： object detection

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Marine Fish object Detection Based on YOLOv5 and Attention Mechanism 19

Marine Fish Object Detection Based on YOLOv5 and Attention M...

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作者： Chen, Lulu Zang, Zhaoxiang Huang, Tianxing Li, Zhao China Three Gorges University Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering Hubei Yichang China Guangdong Zhanjiang China

ISBN: (纸本)9798350346558

Automatic fish object detection methods based on computer vision have been widely used in recent years. In this paper, a YOLOv5s marine fish detection method that integrates attention mechanisms is proposed, which has alleviated the issue of misdetections and omissions caused by the shape, color, and size of the marine fish object. First, the multi-scale clustering method is used to recalculate the anchor box for matching the dataset. then, the channel attention module is added to the feature extraction network of YOLOv5s by using the lightweight attention ECA-Net to obtain important feature information. Meanwhile, the spatial attention module SSA is used to enhance the edge feature information and improve detection accuracy. To further increase the generalization of the detection model, the DropBlock regularization method is added to sparse the features extracted from the backbone network to lessen the overfitting problem. the network is trained and tested using a combination of two publicly available datasets and a self-built dataset with rich samples covering complex living environments of marine fishes. Experiments demonstrate that our method can effectively increase the accuracy of fish object detection while also maintaining the speed of object detection. © 2022 ieee.

关键词： object detection

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Roles, tasks and skills of the enterprise architect in the VUCA world 25

Roles, tasks and skills of the enterprise architect in the V...

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25th ieee international enterprise distributed object computing conference (ieee EDOC)

作者： Ullrich, Andre Bertheau, Clementine Wiedmann, Miriam Sultanow, Eldar Koerppen, Tim Bente, Stefan Univ Potsdam Dept Business Informat Potsdam Germany Capgemini Business Technol Solut Cologne Germany Capgemini Capgemini Nuremburg Nurnberg Germany Tech Hsch Koln Fac Comp Sci & Engn Sci Cologne Germany

ISBN: (纸本)9781665444880

For the last 20 years, enterprise architecture management (EAM) was primarily an instrument for harmonizing and consolidating IT landscapes and is lived as a transformation and governance discipline. It, however, is rather related to IT strategy than aligned to the actual corporate strategy and the work of the enterprise architect is characterized by tasks like prescribing, monitoring, documenting, and controlling. As digital transformation continues apace, companies are facing new challenges that lead to a volatile, uncertain, complex, and ambiguous (VUCA) world. To face these challenges, vision, understanding, clarity and agility allow to anticipative and implement necessary changes. this, of course, has implications for the role of the enterprise architect. S/he needs to start actively supporting innovation and taking more of an advisory role instead of just being driven by the current state of the enterprise architecture. this paper investigates the role of the enterprise architect in the VUCA world. Based on current literature and expert interviews, a survey was conducted among consultants who work as (or with) enterprise architects. Survey results include the evaluation of statements on current tasks of enterprise architects, their influence on projects and companies as well as future requirements on the roles of the enterprise architect. the results from the survey were synthesized with the findings from literature to derive the roles, tasks and skills of enterprise architect in the VUCA world.

关键词： enterprise architecture management skills roles enterprise architect VUCA

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Effects of Artificial Intelligence on enterprise Architectures - A Structured Literature Review 25

Effects of Artificial Intelligence on Enterprise Architectur...

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25th ieee international enterprise distributed object computing conference (ieee EDOC)

作者： Rittelmeyer, Jack Daniel Sandkuhl, Kurt Univ Rostock Inst Comp Sci Rostock Germany

ISBN: (纸本)9781665444880

Artificial Intelligence (AI) is one of the key drivers of digital transformation and challenges enterprises to adapt to its various requirements. Many companies fail to implement AI applications or have significant trouble because of data or process requirements. the changes in a company resulting from the implementation of AI applications can vary from small data format changes over a restructuring of its application landscape to the implementation or deletion of whole business processes or roles. thus, the implementation of AI applications can significantly impact a company's enterprise architecture (EA). We argue that research could facilitate the adoption of AI and help to preserve AI projects from failing. To determine what further research is necessary, this paper seeks to give an overview of the current state-of-the-art of research on the effects of AI applications on EA. For this purpose, we performed a structured literature review (SLR), formulating inclusion and exclusion criteria, developing several search strings, applying them to four scientific databases, performing a forward and backwards search and summarizing the key findings. the (1) performance of the literature review and the (2) discussion of its findings are the main contributions of this paper, identifying a research gap as no concrete research about the effects of AI applications on enterprise architectures could be found. However, a handful of papers in the area of AI and EAM are discovered that endorse the need for further research.

关键词： Artificial Intelligence Digital Transformation enterprise Architecture enterprise Architecture Management Structured Literature Review

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object Detection Algorithm Based on Channel-Spatial Fusion Cascade Attention 8

Object Detection Algorithm Based on Channel-Spatial Fusion C...

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8th ieee international conference on Cloud computing and Intelligence Systems, CCIS 2022

作者： Mao, Guojun Liao, Guanyi Zhu, Hengliang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fuzhou350118 China Fujian University of Technology Fuzhou350118 China

ISBN: (纸本)9781665477352

To solve the problem of low accuracy and high leakage rate of small object detection in a one-stage object detection model, a cascade attention mechanism (CAtt) is proposed. Cascading attention integrates channel attention and spital attention mechanisms that can be flexibly embedded into any object detection model, such as YoloV4, to improve the performance of the object detection model. the attention mechanism is perfected from two aspects: one is to integrate channel attention and spatial attention respectively so that the two are more complementary. Secondly, by introducing the skipping connection mechanism, the shallow detail information is connected with the deep semantic information, to solve the problem of information loss caused by the multiple convolutions of the model. Four typical attention mechanisms were selected to compare public datasets such as PASCAL VOC2007 and PASCAL VOC2012. A large number of experimental results show that this method significantly improves the performance of the object detection model, especially for the PASCAL VOC2007. Embedding the method in YoloV4 resulted in a 4.77% increase in the mAP index of the original model. © 2022 ieee.

关键词： object detection

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