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检索条件"任意字段=Knowledge-Based Software Engineering Conference"

共 17481 条记录，以下是721-730 订阅

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A BASIC FORMAL ONTOLOGY-based ONTOLOGICAL MODELING FOR PLAN AND OCCURRENCE, A BIOMANUFACTURING PROCESS VERIFICATION USE CASE

A BASIC FORMAL ONTOLOGY-BASED ONTOLOGICAL MODELING FOR PLAN ...

引用

ASME 2024 International Design engineering Technical conferences and Computers and Information in engineering conference, IDETC-CIE 2024

作者： Šormaz, Dušan Seeharit, Saruda Kulvatunyou, Boonserm Drobnjaković, Miloš Department of Industrial and Systems Engineering Ohio University AthensOH United States Engineering Laboratory National Institute of Standards and Technology GaithersburgMD United States

ISBN: (纸本)9780791888353

Biomanufacturing has gained significant importance in recent years due to its role in developing new medications, handling pandemics, and increasing the well-being of human populations. The nature of biochemical processes requires complex planning and control, with many controlled and non-controllable variables that impact the quality of bioproducts. Representing biomanufacturing process knowledge, control models, and actual occurrences in coherent ontologies could aid both humans and computers in dealing with the complexity. However, there is a lack of such coherent ontologies. Even though the Industrial Ontology Foundry (IOF) Core ontology has provided a groundwork based on the widely used Basic Formal Ontology (BFO) for such ontological requirements, there are still insufficient constructs and clear guidance on the representation of digital artifacts and their correspondences to the physical counterparts. This paper presents a framework to extend the IOF Core to address the gap. The framework is founded on establishing a counterpart (CR) relation pattern presented in our previous paper. Counterpart relation was selected for its ability to facilitate a more intuitive and concise representation of many kinds of digital artifacts (e.g., planned, designed) and physical entities (e.g., planning process, manufacturing process). We validated the approach with a process verification of a fed-batch bioreactor operation. The paper started by defining the use case requirement, which was followed by an ontology development. A knowledge graph of the bioprocess plan and occurrences of processes in the plan was then instantiated. Competency questions were used to concretize the ontology requirement from the use case, and subsequently, an executable set of queries was created from them and was used to computationally validate the ontology against the requirement. The GraphDB tool was used to support the validation. The result of this research not only showed that the CR pattern

关键词： Smart manufacturing

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Smart and Adaptive Routing Architecture: An Internet-of-Things Traffic Manager based on Artificial Neural Networks

Smart and Adaptive Routing Architecture: An Internet-of-Thin...

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1st IEEE International conference on software Services engineering (IEEE SSE)

作者： Amiri, Amirali Zdun, Uwe Univ Vienna Software Architecture Grp Doctoral Sch Comp Sci Vienna Austria Univ Vienna Software Architecture Grp Vienna Austria

ISBN: (纸本)9798350340754

Many studies have been performed on integrating the Internet of Things (IoT) with cloud services. As these systems become widely used, quality metrics are of concern. For example, users might specify access control to restrict their sensitive data being processed in the cloud. Routers, e.g., API gateways, message brokers, or sidecars, can provide this access control by blocking or routing device data to a specific cloud service. However, a static routing application might not suit the dynamic behavior of IoT applications well. For example, in a centralized schema, where all device data is routed to a component for control checking, performance can be an issue. On the other hand, distributed routing can harm the reliability of a system, as device data might be lost due to an unresponsive service. We present the Smart and Adaptive Routing (SAR) architecture that creates an optimal reconfiguration solution using a deep neural network based on the quality metrics of an IoT application. To design our architecture, we give a background of the published studies and a review of the gray literature, e.g., practitioner blogs, to categorize the knowledge in the domain of IoT-cloud traffic management. We systematically evaluate our approach in an extensive evaluation of 4500 cases and compare SAR with an empirical data set of 1200 hours. The results show that our approach significantly improves quality-of-service measures by adapting the IoT-cloud system at runtime.

关键词： Self-Adaptive Systems Dynamic Routing Architectures Internet of Things Reliability and Performance Trade-Offs IoT-Cloud Traffic Management Artificial Neural Networks

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Certificateless Aggregate Signature Without Trapdoor for Cloud Storage 19th

Certificateless Aggregate Signature Without Trapdoor for Clo...

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19th International conference on Security and Privacy in Communication Networks

作者： Dong, Yingjie Liao, Yongjian Zhang, Zhishuo Huang, Wen Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu Peoples R China Sichuan Univ Chengdu Peoples R China

ISBN: (纸本)9783031649479;9783031649486

In this paper, we propose a lattice-based certificateless signature scheme and certificateless aggregate signature which can be used to verify a large number of signatures simultaneously efficiently. To improve the security of our scheme, we have implemented our signature algorithm without trusted third parties. The security of our proposed signature algorithm can be reduced to the SIS problem under the random oracle model. Moreover, our construction only needs matrix multiplication and rejection sampling operation, so the algorithm is naturally simple and efficient. Besides, we've done some experiments using the NTL library, indicating our scheme has less time overhead and storage overhead than other schemes. To our best knowledge, we propose the first certificateless aggregate signature without trapdoors.

关键词： Certificateless Aggregate Signature Lattice

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Research on adaptive positioning system: a simplified base station scheme based on UWB-PDOA technology 4

Research on adaptive positioning system: a simplified base s...

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4th International conference on Big Data and Artificial Intelligence and software engineering, ICBASE 2023

作者： Huang, Xin Zhang, Chengwei Wei, Zhouwang Jiang, Hao State Grid Fujian Ecomomic Research Institute Fuzhou China Fuzhou University College of Electrical Engineering and Automation Fuzhou China

ISBN: (纸本)9798350329490

This paper presents an adaptive UWB-PDOA positioning system that overcomes limitations of traditional multi-base station methods. By leveraging UWB-PDOA technology and ESP32 signal strength adaptation, the system reduces reliance on environmental deployment while improving accuracy and stability. A prior knowledge base is created by integrating environmental and target height information. Adaptive positioning adjusts confidence weights of base stations using sensor data, leading to enhanced accuracy. Experimental results demonstrate high accuracy and stability in both LOS and NLOS environments. In conclusion, this paper introduces an adaptive UWB-PDOA positioning system that effectively overcomes limitations of traditional multi-base station methods. © 2023 IEEE.

关键词： Base stations

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Flexible Memory Rotation (FMR): Rotated Representation with Dynamic Regularization to Overcome Catastrophic Forgetting in Continual knowledge Graph Learning

Flexible Memory Rotation (FMR): Rotated Representation with ...

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2024 IEEE International conference on Big Data, BigData 2024

作者： Zhu, Lijing Jeon, Dong Hyun Sun, Wenbo Yang, Li Xie, Yixin Niu, Shuteng Bowling Green State University Computer Science Department Bowling Green United States University of Michigan Transportation Research Institute Ann Arbor United States University of North Carolina at Charlotte Computer Science Department Charlotte United States Kennesaw State University College of Computing and Software Engineering Marietta United States

ISBN: (纸本)9798350362480

As a special type of knowledge Graph (KG), Continual knowledge Graph Learning (CKGL) plays a pivotal role in various areas such as recommendation systems, search engines, and personalized services, where knowledge dynamically evolves. A challenging problem in CKGL is catastrophic forgetting, where models forget previously learned knowledge upon being trained on new data. To overcome the challenge, this study proposes Flexible Memory Rotation (FMR), a dual-level regularization technique that focuses on both parameter level and structural level. Our idea is inspired by the natural human learning process, which tends to memorize correctly learned knowledge, leverage the learned to acquire new knowledge, and refine incorrectly learned knowledge with newly obtained information. Commonly, existing regularization-based methods fail to mimic this human nature by having a fixed constraint strategy for all model parameters. To this end, the proposed FMR offers flexible constraints based on qualities of learned knowledge evaluated by the Fisher Information Matrix (FIM). Additionally, we identified a limitation of FIM in CKGL, which is the assumption of independence of time steps does not always hold. To overcome this, FMR rotates the parameter space to diagonalize the FIM. This work has four major contributions: 1) develop a novel regularization technique, FMR, a flexible regularization technique, 2) reveal the unexpected failure of FIM in CKGL and provides an easy remedy via parameter space rotation, 3) the comparison experiments on four benchmark datasets designed for CKGL demonstrates improvement over various state-of-the-art (SOTA) CKGL models, and 4) a comprehensive ablation study investigates each component of the proposed model. The source code is available at https://***/lijingzhu1/FMR. © 2024 IEEE.

关键词： knowledge graph

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A Novel Image Encryption based on Style Transfer 18

A Novel Image Encryption Based on Style Transfer

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18th International conference on Intelligent Systems and knowledge engineering, ISKE 2023

作者： Zhou, Wanyi Lu, Yujin Wang, Rui Wang, Qi Zheng, Jeffrey National Pilot School of Software Yunnan University Kunming China

ISBN: (纸本)9798350318401

This paper introduces an image encryption scheme that combines a style transfer model with chaotic encryption, offering the adaptability of deep learning encryption and the randomness of chaos. During style transfer, a noise image is creatively treated as the style image, while the plaintext image serves as the content image, resulting in a Noise-Style image. Style features of the plaintext are extracted for decryption. The Logistic map is found to be effective in encrypting Noise-Style images, and the Henon map enhances security. The algorithm's key consists of style features and a chaotic key. This approach integrates deep learning into traditional chaotic encryption, making it more complex and secure. Numerical simulations and experiments confirm its feasibility and effectiveness, especially in resisting noise attacks, highlighting its robustness. © 2023 IEEE.

关键词： Chaotic systems

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Learning-based Dichotomy Graph Sketch for Summarizing Graph Streams with High Accuracy 1

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16th International conference on knowledge Science, engineering and Management (KSEM)

作者： Li, Ding Li, Wenzhong Chen, Yizhou Zhong, Xu Lin, Mingkai Lu, Sanglu Nanjing Univ State Key Lab Novel Software Technol Nanjing 210023 Peoples R China

ISBN: (数字)9783031402869

ISBN: (纸本)9783031402852;9783031402869

Graph stream data is widely applied to describe the relationships in networks such as social networks, computer networks and hyperlink networks. Due to the large volume and high dynamicity of graph streams, several graph sketches were proposed to summarize them for fast queries. However, the existing graph sketches suffer from low performance on graph query tasks due to hash collisions between heavy and light edges. In this paper, we propose a novel learning-based Dichotomy Graph Sketch (DGS) mechanism, which adopts two separate graph sketches, a heavy sketch and a light sketch, to store heavy edges and light edges respectively. DGS periodically obtains heavy edges and light edges in a session of a graph stream, and use them as training samples to train a deep neural network (DNN) based binary classifier. The DNN-based classifier is then utilized to decide whether the upcoming edges are heavy or not, and store them in different graph sketches accordingly. With the learnable classifier and the dichotomy graph sketches, the proposed mechanism can resolve the hashing collision problem and significantly improve the accuracy for graph query tasks. We conducted extensive experiments on three real-world graph stream datasets, which show that DGS outperforms the state-of-the-art graph sketches in a variety of graph query tasks.

关键词： Sketch Graph sketch Deep learning Graph stream

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Additive Manufacturing, Reverse engineering and Metrology to support mechanical design: future developments among the INAF facilities 10

Additive Manufacturing, Reverse Engineering and Metrology to...

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conference on Ground-based and Airborne Instrumentation for Astronomy X

作者： Cianniello, Vincenzo De Caprio, Vincenzo Eredia, Christian Cascone, Enrico D'Auria, Domenico Ist Nazl Astrofis INAF Osservatorio Astron Capodimonte Salita Moiariello 16 I-80131 Naples Italy Univ Napoli Federico II DII Via Claudio 21 I-80125 Naples Italy

ISBN: (纸本)9781510675155;9781510675162

In the framework of STILES PNRR Project and as a natural evolution of the INAF Minigrant project on the Integrated approach to the mechanical design for Astronomical Instrumentation, an advanced mechanical engineering laboratory inside the INAF - Observatory of Naples was funded. This facility represents a leap forward in technological research applied to design and development of Ground-based Telescope Instrumentation for the researchers who will use these innovative technologies. The role of the new laboratory for mechanical engineering, in the INAF context, is essentially to support the advanced design, develop prototypes with different Additive Manufacturing 3D printers, maintain state-of-the-art for astronomical instruments and equipment and revamp/retrofit the existent facilities utilizing also the Reverse engineering approach. The real innovation of this laboratory is represented by the technologies and techniques that will be implemented inside of it. Another focus is on Metrology applied to characterize, control and accept the mechanical items designed with 3D CAD software and validated by FEA approach during the design phase. The synergy between these disciplines promises to improve the scientific collaboration and the technological expertise for INAF researchers of Naples. Mechanical engineering is the backbone of the astronomical facilities, always bigger than previous one, and enable astronomers to make groundbreaking discoveries and expand our knowledge of space.

关键词： STILES PNRR MORFEO INAF FDM SLA FEM FEA CAD CAE Metrology Labs National Facility

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Research on Recommendation Algorithm of knowledge Graph Convolutional Networks Integrating User Information and Interest Evolution

Research on Recommendation Algorithm of Knowledge Graph Conv...

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2023 International conference on Image Processing and Computer Vision, IPCV 2023

作者： Zhang, Xiaoming Liu, Shumin Xie, Shubiao Zhang, Yunli Chen, Xingfeng School of Software Engineering Jiangxi University of Science and Technology Jiangxi Nanchang330013 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100101 China

ISBN: (纸本)9781665473941

Existing recommendation Models based on knowledge Graph often only enrich the features of items and don't take into account the impact of user's feature on recommendations, such as user information and changes of user interests. Therefore, a recommendation model based on KGCN called KGCNUIE is proposed in this paper, which integrates users' personal information and long-term and short-term interest preferences of models on the basis of KGCN model to enrich user features and improve recommendation performance. Experimental results show that compared with the KGCN algorithm, the KGCNUIE algorithm improves the AUC by 0.61 % and F1 value by 0.53 % on the MovieLens-1M dataset, and imporves the AUC by 0.54% and F1 value by 0.93% on the Book-Crossing dataset. This demonstrates that the proposed KGCNUIE algorithm achieves certain effectiveness. © 2023 IEEE.

关键词： knowledge graph

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Application of IoT in Smart Metering: A Survey

Application of IoT in Smart Metering: A Survey

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2024 International conference on Electrical and Computer engineering Researches, ICECER 2024

作者： Letsoara, Mokhele Mendu, Bongumsa Monchusi, Bessie Baakanyang University of South Africa Department of Electrical Engineering and Mining Engineering Pretoria South Africa National Transmission Company of South Africa SOC Ltd. Asset Management Department Johannesburg South Africa

ISBN: (纸本)9798331539733

This work presents the findings from a survey conducted on the use of Internet of Things (IoT) in smart metering (SM) for commercial, residential, and industrial settings. Appropriate publications were scientifically identified, selected, and evaluated, primarily concentrating on used methods in IoT in smart metering. The observed mostly used techniques were Energy (BLE) systems, narrow-band Internet of Things (NB-IoT), adaptive multivariate etc. Moreover, results on co-keywords were identified, analyzed, and discussed for IoT in smart metering research using VOSviewer software tool. This paper provides possible imminent research gaps which can be supplementary explored. Thus, this research contributes to the knowledge of literature by providing with a widespread framework of approaches and co-keywords on application of IoT in smart metering. Additionally, this paper will provide alternative approaches that can be used for industrial, residential, commercials application of IoT in SM. Finally, the overall work in this paper will serve as a foundation of records to those researchers involved in studies that are based on IoT in SM. © 2024 IEEE.

关键词： bluetooth low energy Internet of Things smart grid smart metering

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