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Electronics and Renewable Systems (ICEARS), International Conference on

作者： P. Chinnasamy Subashini. B Nijanthan Nijanthan Madasamy Raja. G Devulapally Swetha Sreenivasulu Reddy L Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamilnadu India Department of Data Science and Business Systems School of Computing SRMIST India Computer Science and Engineering Paavai Engineering College Namakkal Tamilnadu India Information Technology Paavai Engineering College Namakkal Tamilnadu India Dept. of Computer Science and Engineering Vaagdevi Engineering College Telangana India Department of Mathematics School of Advanced Sciences Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

The rapid advancement of Blockchain technology has led to its widespread application in several domains of digital activities, such as e-government concerns and monetary security. This article presents a smart contract-based Blockchain solution for protecting intellectual property rights in new product development. The proposed solution effectively tackles the challenges associated with the confidentiality of personally identifiable information, efficiency in storing transaction-related information, as well as cooperation and monitoring in IPR. Initially, we create a mathematical model based on smart contract enabled Blockchain and intelligent contracts. Subsequently, we develop algorithms for Blockchain generation, and intelligent contracts. The system is suitable for protecting IPR in a blockchain network, by implementation of distributed identity authentication and real-time extensible storage. These features enhance the security and expandability of circuit copyright protection based on blockchain technology. The experimental results demonstrate that the suggested algorithm has decreased the cost for communication and enhanced the effectiveness of storing information and administration. Furthermore, it demonstrates resilience against many common attacks such as double-spending assaults, while maintaining low cost and overhead. Additionally, it exhibits a superior level of security in comparison to three other competing algorithms.

关键词： Patents Technological innovation Costs Smart contracts Intellectual property Product development Blockchains Security Protection Resilience

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A linked data application framework to enable rapid prototyping

arXiv

引用

arXiv 2021年

作者： Schröder, Markus Jilek, Christian Dengel, Andreas Smart Data & Knowledge Services Dept. DFKI GmbH Kaiserslautern Germany Computer Science Dept. TU Kaiserslautern Germany

Application developers, in our experience, tend to hesitate when dealing with linked data technologies. To reduce their initial hurdle and enable rapid prototyping, we propose in this paper a framework for building linked data applications. Our approach especially considers the participation of web developers and non-technical users without much prior knowledge about linked data concepts. Web developers are supported with bidirectional RDF to JSON conversions and suitable CRUD endpoints. Non-technical users can browse websites generated from JSON data by means of a template language. A prototypical open source implementation demonstrates its capabilities. Copyright © 2021, The Authors. All rights reserved.

关键词： Rapid prototyping

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dataset generation patterns for evaluating knowledge graph construction

arXiv

引用

arXiv 2021年

作者： Schröder, Markus Jilek, Christian Dengel, Andreas Smart Data & Knowledge Services Dept. DFKI GmbH Kaiserslautern Germany Computer Science Dept. TU Kaiserslautern Germany

Confidentiality hinders the publication of authentic, labeled datasets of personal and enterprise data, although they could be useful for evaluating knowledge graph construction approaches in industrial scenarios. Therefore, our plan is to synthetically generate such data in a way that it appears as authentic as possible. Based on our assumption that knowledge workers have certain habits when they produce or manage data, generation patterns could be discovered which can be utilized by data generators to imitate real datasets. In this paper, we initially derived 11 distinct patterns found in real spreadsheets from industry and demonstrate a suitable generator called data Sprout that is able to reproduce them. We describe how the generator produces spreadsheets in general and what altering effects the implemented patterns have. Copyright © 2021, The Authors. All rights reserved.

关键词： knowledge graph

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UDC-VIT: A REAL-WORLD VIDEO dataSET FOR UNDER-DISPLAY CAMERAS

arXiv

引用

arXiv 2025年

作者： Ahn, Kyusu Kim, JiSoo Lee, Sangik Lee, HyunGyu Ko, Byeonghyun Park, Chanwoo Lee, Jaejin Dept. of Data Science Seoul National University Seoul Korea Republic of Dept. of Computer Science and Engineering Seoul National University Seoul Korea Republic of Research Center Samsung Display Co. Ltd. Yongin Korea Republic of Mobile Display Electronics Development Team Samsung Display Co. Ltd. Yongin Korea Republic of

Under Display Camera (UDC) is an advanced imaging system that places a digital camera lens underneath a display panel, effectively concealing the camera. However, the display panel significantly degrades captured images or videos, introducing low transmittance, blur, noise, and flare issues. Tackling such issues is challenging because of the complex degradation of UDCs, including diverse flare patterns. Despite extensive research on UDC images and their restoration models, studies on videos have yet to be significantly explored. While two UDC video datasets exist, they primarily focus on unrealistic or synthetic UDC degradation rather than real-world UDC degradation. In this paper, we propose a real-world UDC video dataset called UDC-VIT. Unlike existing datasets, only UDC-VIT exclusively includes human motions that target facial recognition. We propose a video-capturing system to simultaneously acquire non-degraded and UDC-degraded videos of the same scene. Then, we align a pair of captured videos frame by frame, using discrete Fourier transform (DFT). We compare UDC-VIT with six representative UDC still image datasets and two existing UDC video datasets. Using six deep-learning models, we compare UDC-VIT and an existing synthetic UDC video dataset. The results indicate the ineffectiveness of models trained on earlier synthetic UDC video datasets, as they do not reflect the actual characteristics of UDC-degraded videos. We also demonstrate the importance of effective UDC restoration by evaluating face recognition accuracy concerning PSNR, SSIM, and LPIPS scores. UDC-VIT enables further exploration in the UDC video restoration and offers better insights into the challenge. UDC-VIT is available at our project site. © 2025, CC BY-NC-SA.

关键词： Restoration

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Ontology-Based Method for Semantic Association Rules

Ontology-Based Method for Semantic Association Rules

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IEEE India Conference (INDICON)

作者： Abhilash C B Kavi Mahesh Dept. of Computer Science and Engineering Indian Institute of Information Technology Dharwad Dharwad India Dept. of Data Science and Intelligent Systems Indian Institute of Information Technology Dharwad Dharwad India

ISBN: (纸本)9781665452724

Finding interesting association rules is a popular and current topic in data mining. The Apriori family of algorithms is built around two rule extraction measures: support and confidence. Even though these two measures are easy to compute, they yield many rules, the majority of which are redundant and may not be of interest to the user. Also, by themselves, support and confidence do not generate strong rules. Additional measures are required to mine interesting facts from data. Ontologies have become the fundamental building blocks for structuring and formalizing data. With the semantic structuring of information, the implicit relationship between data elements makes the analyst get important facts from the data. Our study proposes a novel framework for interestingness in data by combining domain ontology with semantic interestingness measures. The ontology-based method infers rules that are semantically enriched and strong. We analyze the quality of the rule considering the factors defined by the domain experts. It is observed that our methodology generates semantically enriched rules that are more acceptable to domain experts.

关键词： COVID-19 Current measurement Semantics knowledge based systems Influenza Ontologies Resource description framework

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Redefining the Landscape of Wire Arc Additive Manufacturing: Pioneering Innovations for Residual Stress Mitigation and Process Efficiency

Redefining the Landscape of Wire Arc Additive Manufacturing:...

引用

Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Falah Hassan Abdullah Kilaru Aswini Manjunatha H Pal Thethi Ashish Parmar B. Ganga Bhavani Department of Forensic Sciences College of Science National University of Science and Technology Dhi Qar Iraq Institute of Aeronautical Engineering Dundigal Hyderabad Department of Mechanical Engineering New Horizon College of Engineering Bangalore Lovely Professional University Phagwara Knowledge Park II Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh Dept. of IT St. Martin’s Engineering College Secunderabad Telangana India

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

This study introduces a comprehensive framework for Wire Arc Additive Manufacturing (WAAM) optimization, incorporating five key algorithms: Adaptive Layer Thickness Control, In-Situ Stress Monitoring, Dual-Wire Deposition, Thermal Management Strategies, and Machine Learning for Process Control. The Adaptive Layer Thickness Control Algorithm dynamically adjusts layer thickness based on geometric features and real-time feedback, contributing to stress mitigation. The In-Situ Stress Monitoring Algorithm ensures real-time stress distribution optimization. The Dual-Wire Deposition Algorithm introduces simultaneous deposition of two materials, optimizing multi-material properties. Thermal Management Strategies Algorithm focuses on controlling temperature gradient and adaptive cooling strategies. Machine Learning for Process Control Algorithm integrates input from preceding algorithms to predict optimal parameters, ensuring adaptive layer control and overall process optimization. Evaluation against existing methods demonstrates superior outcomes in residual stress reduction, geometric accuracy improvement, material integrity enhancement, process stability, build rate improvement, and energy efficiency. Visualizations and comparative tables confirm the proposed method’s holistic excellence in WAAM.

关键词： Technological innovation Machine learning algorithms Heuristic algorithms Process control Three-dimensional printing Prediction algorithms Thermal management

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XCoref: Cross-document coreference resolution in the wild

arXiv

引用

arXiv 2021年

作者： Zhukova, Anastasia Hamborg, Felix Donnay, Karsten Gipp, Bela Data and Knowledge Engineering University of Wuppertal Germany Dept. of Computer Science University of Konstanz Germany Dept. of Political Science University of Zurich Switzerland Heidelberg Academy of Sciences and Humanities Germany

datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities with strict coreference relations. They lack, however, annotating and resolving coreference mentions with more abstract or loose relations that may occur when news articles report about controversial and polarized events. Bridging and loose coreference relations trigger associations that may lead to exposing news readers to bias by word choice and labeling. For example, coreferential mentions of "direct talks between U.S. President Donald Trump and Kim" such as "an extraordinary meeting following months of heated rhetoric" or "great chance to solve a world problem" form a more positive perception of this event. A step towards bringing awareness of bias by word choice and labeling is the reliable resolution of coreferences with high lexical diversity. We propose an unsupervised method named XCoref, which is a CDCR method that capably resolves not only previously prevalent entities, such as persons, e.g., "Donald Trump," but also abstractly defined concepts, such as groups of persons, "caravan of immigrants," events and actions, e.g., "marching to the U.S. border." In an extensive evaluation, we compare the proposed XCoref to a state-of-the-art CDCR method and a previous method TCA that resolves such complex coreference relations and find that XCoref outperforms these methods. Outperforming an established CDCR model shows that the new CDCR models need to be evaluated on semantically complex mentions with more loose coreference relations to indicate their applicability of models to resolve mentions in the "wild" of political news articles. © 2021, CC BY.

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Third Generation Security System for Face Detection in ATM Machine Using Computer Vision

Third Generation Security System for Face Detection in ATM M...

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Computer, Power and Communications (ICCPC), International Conference on

作者： S Sridevi K.M. Monica G. A Senthil R. Prabha A. Sathya J Ramya Dept. of Computer Science and Engineering Sri Ramachandra Engineering and Technology Chennai India Dept. of Computer Science and Engineering VIT Chennai Campus Chennai India Dept. of Information Technology Agni College of Technology Chennai India Dept. of Electronics and Communication Engineering Sri Sai Ram Institute of Technology Chennai India Dept. of Artificial Intelligence and Data Science Sri Sai Ram Institute of Technology Chennai India Dept. of Computer Science and Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS) Chennai India

A workflow is proposed for the detection of unauthorized persons in an ATM. Certain assumptions, including the context of identification are made by training their features and storing the datasets. However, not every individual will be a suspect. Suspicious activity on ATMs that are located in remote areas and to reduce the risk of fraudulent transactions. such as using another person's card to withdraw money etc., Various video survey and image processing have been discussed in relation to surveillance methods. It discusses the various processes, preprocessing, classification, feature extraction and the corresponding video processing methods.

关键词： Training Online banking Shape Face recognition Surveillance Prediction algorithms Feature extraction

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Multi-modal Underwater Acoustic Target Recognition

Multi-modal Underwater Acoustic Target Recognition

引用

Computer, Big data and Artificial Intelligence (ICCBD+AI), International Conference on

作者： Tianxiang He Rui Xiang Junlin Zhou Duanbing Chen Sheng Feng Jie Yang Chengdu Union Big Data Technology Inc. Chengdu China School of Computer Science and Engineering UESTC Chengdu China Dept. 804 Sichuan Jiuzhou Electric Co. Ltd. Mianyang China

ISBN: (数字)9798331533991

ISBN: (纸本)9798331534004

Underwater acoustic target recognition (UATR) has gained significant attention across various fields in recent years. However, traditional UATR methods, which primarily rely on data from a single sensor, have limitations in fully capturing target characteristics. This constraint ultimately impacts the accuracy and robustness of recognition. This paper presents a multi-modal UATR method that fuses data from two different sensors, thereby improving underwater target recognition accuracy. Additionally, a new training framework is proposed to facilitate the learning of consistent feature representations across diverse data sources, allowing for more effective capture of the intrinsic characteristics of acoustic data. Experimental results demonstrate that the method has positive effectiveness under various Signal-to-Noise Ratio (SNR) conditions and achieves an improvement in recognition accuracy ranging from 0.95% to 8.33%.

关键词： Training Accuracy Target recognition Fuses Soft sensors Self-supervised learning data models Robustness Underwater acoustics Signal to noise ratio

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Transforming Wire Arc Additive Manufacturing: A Novel Approach to Achieving High Deposition Rates with Reduced Costs

Transforming Wire Arc Additive Manufacturing: A Novel Approa...

引用

Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Amandeep Nagpal V Alekhya B Swathi A Sravani Ashwani Kumar Maytham Razaq Shleghm Lovely Professional University Phagwara Institute of Aeronautical Engineering Dundigal Hyderabad Department of Information Science Engineering New Horizon College of Engineering Bangalore AP Dept. of IT St. Martin‘s Engineering College Secunderabad Telangana India Knowledge Park II Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh College of Pharmacy National University of Science and Technology Dhi Qar Iraq

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

This study introduces a suite of algorithms designed to revolutionize Wire Arc Additive Manufacturing (WAAM) by addressing critical aspects such as deposition rates, material efficiency, precision, cost-effective heat management, and dynamic build time optimization. The presented algorithms-Adaptive Parameter Optimization (APO), Material Efficiency Enhancement (MEE), Precision Maximization (PMX), Cost-Effective Heat Management (CEHM), and Dynamic Build Time Optimization (DBTO)offer a holistic and dynamic approach to WAAM optimization. APO dynamically adjusts WAAM parameters, ensuring optimal deposition rates. MEE optimizes material efficiency based on target values, promoting cost-effective material utilization. PMX enhances precision through dynamic adjustments. CEHM integrates heat management with cost considerations, achieving efficiency while minimizing costs. DBTO optimizes build time dynamically, ensuring efficient time utilization. Comparative evaluation tables and visualizations demonstrate the proposed method’s superiority in deposition rates, material efficiency, precision, scalability, cost-effectiveness, and adaptability. The dynamic nature of the algorithms ensures continuous optimization, leading to enhanced overall performance in WAAM. The study lays the foundation for future advancements in WAAM optimization, contributing to the evolution of advanced manufacturing techniques.

关键词： Heating systems Visualization Technological innovation Costs Heuristic algorithms Scalability Aerodynamics

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