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检索条件"任意字段=International Conference on Data and Knowledge Systems for Manufacturing and Engineering"

共 37467 条记录，以下是4721-4730 订阅

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Enabling Semantic Interoperability of Asset Administration Shells Through an Ontology-based Modeling Method 22

Enabling Semantic Interoperability of Asset Administration S...

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ACM/IEEE 25th international conference on Model Driven engineering Languages and systems (MODELS)

作者： Huang, Yining Dhouib, Saadia Medinacelli, Luis Palacios Malenfant, Jacques Univ ParisSaclay CEA List Palaiseau France Sorbonne Univ CNRS Lab Informat Paris 6 LIP6 Paris France

ISBN: (纸本)9781450394673

Digital twin technology establishes the future development vision for Industry 4.0, and is also an important exploration direction for the Model-Driven engineering (MDE) paradigm. Because it builds a more flexible and communicative production system through models that spans life cycle, hierarchy and architecture. The standard proposed under the concept of Industry 4.0, the Asset Administration Shell (AAS), provides a syntactic interoperability interface for all assets involved in smart factories. However, there is still a need to fill the gap regarding semantic interoperability, in order to allow efficient interactions between Industry 4.0 components. Ontologies are a good candidate because they provide formal semantics expressed using a knowledge representation language, and in addition, there are many associated mature tools for reasoning and inference. Therefore, we propose a modeling approach that provides semantic interoperability for AAS-based digital twins using ontologies.

关键词： Model-Driven engineering Digital Twins Ontology Industry 4.0 Asset Administration Shell Semantic Interoperability Smart manufacturing

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A Resonance to the Secure Image Transmission via Cryptographic and Steganographic Approaches

A Resonance to the Secure Image Transmission via Cryptograph...

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knowledge engineering and Communication systems (ICKECS), international conference on

作者： K M Sunil Kumar M K Shyla Kalpataru Institute of Technology Tiptur India Sri Siddhartha Institute of Technology Tumukur India

ISBN: (数字)9798331537012

ISBN: (纸本)9798331537029

The fast expansion of digital communication and data transfer in resource-limited settings, including IoT, cloud computing, and embedded systems, has heightened the necessity for secure picture transmission. Adaptive cryptography and steganography algorithms have arisen as efficacious answers to the simultaneous concerns of efficiency and security. This study emphasizes novel approaches, including hybrid cryptographic frameworks, lightweight secret-sharing techniques, diffusion-centric steganography, and chaotic map-based encryption. It offers an extensive comparative study of techniques, results, and limits, highlighting performance indicators including robustness, computing efficiency, and resilience to steganalysis. Despite considerable progress, issues like as processing overhead, scalability, and susceptibility to future attacks remain. This study intends to be a primary reference for researchers and practitioners, highlighting trends, shortcomings, and prospects for future endeavors in secure picture transmission designed for resourceconstrained settings.

关键词： Resistance Steganography Scalability Image communication data transfer Robustness Resonance Real-time systems Cryptography Resilience

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How to Position Your Gateway for Failure: The Ten Don'ts of Gateway Design 58

How to Position Your Gateway for Failure: The Ten Don'ts of ...

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58th Hawaii international conference on System Sciences, HICSS 2025

作者： Gesing, Sandra Brandt, Steven R. Bradley, Shannon Villegas Martinez, Braulio M. Kee, Kerk Cleveland, Sean Smith, Jack University of California San Diego United States Louisiana State University United States National Center for Supercomputing Applications United States Mexico Texas Tech University United States University of Hawaii United States

ISBN: (纸本)9780998133188

Science gateways are accelerators for science and education, providing user-friendly access to powerful computational resources and data analysis tools. Sustained science gateways frameworks such as Hubzero, Tapis, and Galaxy demonstrate the potential for gateways to revolutionize scientific exploration. However, despite initial promise, many gateway projects struggle to transition from prototypes to sustainable, long-term services. Well-intentioned, yet ultimately unsuccessful, gateways are part of the scientific landscape. This raises a critical question: what factors contribute to the demise of science gateways, and how can we avoid these pitfalls to ensure the success of future endeavors? This paper delves into the ten most common pitfalls that lead to science gateway failure. By analyzing these roadblocks, we aim to equip new and developing gateway initiatives with suggestions for long-term success. Our research draws on the collective experiences of numerous gateway projects. We identified critical areas where focused attention and strategic planning are essential. This knowledge will enable the development of good practices that nurture vibrant gateway communities and ensure the long-term sustainability of these valuable research tools. © 2025 IEEE Computer Society. All rights reserved.

关键词： Usability engineering

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Mapping the environment in a closed room using a mobile robot 27

Mapping the environment in a closed room using a mobile robo...

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27th international conference on knowledge Based and Intelligent Information and engineering Sytems, KES 2023

作者： Pecolt, Sebastian Blazejewski, Andrzej Królikowski, Tomasz Kaminski, Kazimierz Faculty of Mechanical Engineering Koszalin University of Technology Sniadeckich Str. 2 Koszalin75-453 Poland

This paper proposes the author's design of a mobile robot intended for creating a two-dimensional map of the environment. The first part of the paper describes the scope of automated systems called robots. On this basis, the design assumptions of the author's robot were defined, the components used in the construction are shown, the operation of the Robot Operating System (ROS) and the packages used in this robot control system are presented. The main idea, which was to govern the project was its low manufacturing cost. Thus, the use of the optical system of the Kinect device. As a result. the operation of the algorithm controlling the robot via the ATmega328 microcontroller is demonstrated. The results of the experimental verification of the robot's performance are presented in the form of two-dimensional maps of the rooms in which the experiments were carried out. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： ATmega328 Kinect Mobile robot Robot Operating System

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Energy Cost Characteristics of a Micro-Wind Power System Based on Different Capacity Factor: A Case Study of Locations in Nigeria 5th

Energy Cost Characteristics of a Micro-Wind Power System Bas...

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5th international conference on Advances in manufacturing and Materials engineering, ICAMME 2022

作者： Kunya, Bashir Isyaku Alhassan, Yusuf Auwal, S.T. Tambaya, Magaji Kurniawan, D. Ramesh, S. Department of Mechanical Engineering Faculty of Engineering Kano University of Science and Technology P.M.B 3244 Kano State Wudil Nigeria Faculty of Engineering Universiti Teknologi Brunei Tungku Highway Gadong1410 Brunei Center of Advanced Manufacturing and Materials Processing Department of Mechanical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9789811995088

A significant disadvantage of wind power systems (WPS) on electricity production is certainly their relatively high capital cost. However, a WPS may have lower levelized cost of energy (LCOE) than a fossil fuel source depending on site location and design of the power plant. LCOE from WPS depends on its capacity factor, which depends on the design specifications of a wind turbine model installed and the location's weather conditions. This work studied the cost characteristics of a micro-wind power system using different capacity factor based on locations with low average wind speed in Nigeria. Wind speed data was used to determine WPS's capacity factor for 16 locations in Nigeria. The levelized cost of energy of wind turbine system was obtained from a previous study on the cost of micro-wind turbines for a particular location and related to locations considered in this work. Based on the results obtained for the different locations, it was found that LCOE decreases non-linearly with increasing capacity factor of the WPS. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Location

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Empowering Student Entrepreneurship Through IoT-Enabled Industrial Electronics

Empowering Student Entrepreneurship Through IoT-Enabled Indu...

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international conference on Computational Innovations and engineering Sustainability (ICCIES)

作者： Hassan Safi Jasim Ahmede Jasim Marwan Aziz Mohammed Nema H. Hameed Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq Al-Nisour University College Baghdad Iraq Department of Computer Engineering College of Engineering Knowledge University Erbil Iraq Department of Anesthesia Techniques Uruk University Baghdad Iraq

ISBN: (数字)9798331536695

ISBN: (纸本)9798331536701

Education is defined as the process of learning new things and sharing that knowledge with other people. The term "educated" refers to someone who has attended a school and received either formal training or classroom instruction. Industrial electronics keeps an eye on control and power management systems. These instruments not only measure the electrical characteristics of components but also help us understand the production process. By the end of the course, students will be able to operate and program machine controls, as well as lay out and install electronic systems. A number of issues have been raised, including the disdain for social relationships and the capacity of people to acquire heating. It is possible that manufacturing might become more effective and productive with less human effort with the help of IoT technologies. Even with data processed and stored in IoT devices, the system can continue to function normally. As part of their education in industrial control and automation, engineers participating in the EIE-IoT program talk about the tools and techniques they employed. Industrial electronics are used in many different industries to increase efficiency and productivity. These industries include transportation, energy, agriculture, mining, oil and chemicals, semiconductor production, and many more. The paper utilizes this information to bolster the concept of new technological incubators and classes in technical entrepreneurship. All throughout the world, its history, present, and future are analyzed in the study. Finally, IE training takes the long view. The article presents experimental results that demonstrate various ratios: 82.35% for educational knowledge development, 80.4% for power electronics, 78.9% for management, 83.7% for attitude self-learning capacity, 91.2% for wearable sensors, and 92.5% for industrial electronics.

关键词： Training Learning systems Technological innovation Automation Industrial control Entrepreneurship Transportation Power electronics Internet of Things Wearable sensors

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Adaptive Neural Network-Based Improved Fabric Defect Detection Scheme 12th

Adaptive Neural Network-Based Improved Fabric Defect Detecti...

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12th international conference on Recent Trends in Computing, ICRTC 2024

作者： Prabha, P. Anantha Abirami, S. Varshini, N. Amirtha Garishma, K. Priya, M. Deva Karthick, S. Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Tamil Nadu Coimbatore India Department of Computer Science and Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Department of Computer Science and Engineering Karpagam College of Engineering Tamil Nadu Coimbatore India Department of Computer Science and Engineering Delhi - NCR Campus SRM Institute of Science and Technology Uttar Pradesh Ghaziabad India

ISBN: (纸本)9789819789450

Efficient detection of defects in fabric plays a dominant role in automating quality control. It significantly enhances efficiency as well as accuracy of quality assurance in textile manufacturing. Skilled humans who physically examine defective designs in numerous sectors use traditional defect detection techniques. The main drawbacks of manual methods include deficiency of concentration, inaccuracy, weariness and increased time consumption. Computer Vision (CV) and Digital Image Processing (DIP) techniques may be efficient in overcoming these shortcomings. The proposed approach involves data acquisition to record images which are subsequently pre-processed using histogram equalization to improve the defective area. A distinctive Neural Network (NN) is used for defect detection. This method improves precision and efficiency in identifying defects. The proposed method is built using Adaptive NNs (ANNs) along with Radial Basis Functions (RBFs) and is aimed at revolutionary identification of fabric flaws. The networks are built using attributes derived from images segmented using Expectation Maximization (EM) depending on target’s region attributes. As a result, the type of defects is classified based on the extracted features, thus yielding increased detection accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Radial basis function networks

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IMQA: A knowledge Graph Driven Question Answering System for Internal Medicine 8

IMQA: A Knowledge Graph Driven Question Answering System for...

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8th IEEE international conference on Cloud Computing and Intelligence systems, CCIS 2022

作者： Li, Mengzhan Li, Haisheng Wang, Wei Wang, Di Beijing Technology and Business University School of Computer Science and Engineering Beijing100048 China

ISBN: (纸本)9781665477352

The prevention and treatment of internal medicine diseases are a focus of public attention. The emergence of various medical websites makes online consultation a popular trend. knowledge graph can construct the correlation between different knowledge and provide the data support for question answering systems. Therefore, to assist patients with self-diagnosis, a knowledge graph driven question answering system for internal medicine is constructed in this paper. In the implementation, the ontology schema of internal medicine diseases, which is the basis of knowledge graph construction, is designed. Multiple entities and relationships, extracted from the data on professional healthcare websites, are stored in the Neo4j. After the segmentation of the question, the Aho-Corasick automaton algorithm and semantic similarity are applied to entity recognition. The rule-based approach, an accurate way, is used to identify intentions. This intelligent system, which has high value for the treatment of internal medicine diseases, can effectively solve health issues and reduce the cost of the consultation. © 2022 IEEE.

关键词： knowledge graph

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Deep Learning-Based Predictive Skin Disease Diagnosis and Analysis

Deep Learning-Based Predictive Skin Disease Diagnosis and An...

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knowledge engineering and Communication systems (ICKECS), international conference on

作者： Manikundan Karnati Pavan Sai Rohith Kumar Pittala K. Radhika K. Sugamya Department Of Artificial Intelligence and Data Science Chaitanya Bharathi Institute of Technology Hyderabad India Department Of Information technology Chaitanya Bharathi Institute of Technology Hyderabad India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

In modern medical diagnostics, AI integration is crucial for enhancing the prediction or classification of diseases. The primary goal of this project is to develop a multimodal deeplearning system capable of diagnosing skin diseases. The project integrates image analysis for skin conditions and the interpretation of textual descriptions of symptoms, ultimately providing an accurate diagnosis for users. It integrates deep learning and natural language processing to diagnose skin diseases. It Enhances healthcare by providing accurate diagnoses, and remedies and improving accessibility for self-diagnostics.

关键词： knowledge engineering Deep learning Accuracy Image analysis Communication systems Predictive models Skin

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6th international conference on Innovative Computing and Communication, ICICC 2023

6th International Conference on Innovative Computing and Com...

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6th international conference on Innovative Computing and Communication, ICICC 2023

ISBN: (纸本)9789819930098

The proceedings contain 128 papers. The special focus in this conference is on Innovative Computing and Communication. The topics include: Wearable Sensor Based Cloud data Analytics Using Federated Learning Integrated with Classification by Deep Learning Technique;comparison of Decision Tree and Random Forest for Default Risk Prediction;trusted Cloud Service Framework for Cloud Computing Security;HITR-ECG: Human Identification and Classification Simulation System Using Multichannel ECG Signals: Biometric systems Era;brain Disorder Classification Using Deep Belief Networks;Diabetic Retinopathy Detection Using Deep CNN Architecture and Medical Prescription;an Innovative Software engineering Approach to Machine Learning for Increasing the Effectiveness of Health systems;region of Interest and Feature-based Analysis to Detect Breast Cancer from a Mammogram Image;vehicular Ad Hoc Network: A Review;Securing the Networks Against DDoS Attacks Using Blockchain Technology;the Proposed Deep Learning Combined with knowledge Graphs for Fake News Detections on Social Networks;algorithm-Driven Predictive Analysis of Blue-Chip Stocks in the Murky Indian Environment;survey on Crime Analysis, Forecasting, and Prediction Using Machine Learning;soft Computing and data Mining Techniques for Dengue Detection: A Review;Extended HD-MAABE Scheme Supporting Delegation and Revocation for Cloud-based Organizational data Sharing;detection of Open Metal Sites in Metal–Organic Frameworks Using Machine Learning;PCA-Based Feature Selection and Hybrid Classification Model for Speech Emotion Recognition;ANFIS and Kernel Extreme Learning Machine to the Assessment and Identification of Seismic b-value as Precursor;payroll Management Using Blockchain;centric Management of Resources in Modern Distributed Computing;enhancing Security of IoT data Transmission in Social Network Applications.

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