Ontologies as computational artifacts have been seen as a solution to FAIRness due to their characteristics, applications, and semantic competencies. Conceptualizations of complex and vast domains can be fragmented in...
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ISBN:
(纸本)9783031472619;9783031472626
Ontologies as computational artifacts have been seen as a solution to FAIRness due to their characteristics, applications, and semantic competencies. Conceptualizations of complex and vast domains can be fragmented in different ways and can compose what is known as ontology networks. Thus, the ontologies produced can relate to each other in many different ways, making the ontological artifacts themselves subject to FAIRness. The problem is that in the Ontology Engineering process, stakeholders take different perspectives of the conceptualizations, and this causes ontologies to have biases that are sometimes more ontological and sometimes more related to the domain. Besides, usually, Ontology Engineers provide well-grounded reference ontologies, but rarely are they implemented. At the same time, Domain Specialists produce operational ontologies storing large amounts of valid data but with naive ontological support or even without any. We address this problem of lack of consensual conceptualization by proposing a reference conceptual model (O4OA) that considers ontological-related and domain-related perspectives, knowledge, and commitment necessary to facilitate the process of Ontological analysis, including the analysis of ontologies composing an ontology network. Indeed, O4OA is a (meta)ontology grounded in the Unified Foundational Ontology (UFO) and supported by well-known ontological classification standards, guides, and FAIR principles. We demonstrate how this approach can suitably promote conceptual clarification and terminological harmonization in this area through our framework proposal and its case studies.
A transient thermal model and analysis of passive control of annealing process in thermal cycling process to be carried out as part of continuous flow Polymerase Chain Reaction (PCR) is presented. Phase Changing Mater...
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The success and accuracy of analysis and processing of raster images of electronic assemblies entering the machine vision algorithms and models within the electronics manufacturing process depend on parameters of thes...
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The increasing complexity and global competition in various industries have compelled organizations to prioritize quality engineering as a critical factor for success. In recent years, Artificial Intelligence (AI) and...
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The swift advancement of cyber-physical systems (CPSs) across sectors such as healthcare, transportation, critical infrastructure, and energy enhances the crucial requirement for robust cybersecurity measures to prote...
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The swift advancement of cyber-physical systems (CPSs) across sectors such as healthcare, transportation, critical infrastructure, and energy enhances the crucial requirement for robust cybersecurity measures to protect these systems from cyberattacks. The cyber-physical method is a hybrid of cyber and physical components, and a safety breach in the element is central to catastrophic consequences. Cyberattack recognition and mitigation techniques in CPSs include using numerous models like intrusion detection systems (IDSs), access control mechanisms, encryption, and firewalls. Cyberattack detection employing deep learning (DL) contains training neural networks to identify patterns indicative of malicious actions within system logs or network traffic, allowing positive classification and mitigation of cyber-attacks. By leveraging the integral ability of DL methods to learn complex representations, this technique enhances the accuracy and efficiency of detecting diverse and growing cyber-attacks. Thus, the study proposes an automated Cyberattack Detection using Binary Metaheuristics with Deep Learning (ACAD-BMDL) method in a CPS environment. The ACAD-BMDL method mainly focuses on enhancing security in the CPS environment via the cyberattack detection process. The ACAD-BMDL method uses Z-score normalization to scale the input dataset. In addition, the binary grey wolf optimizer (BGWO) model is utilized to choose an optimal feature subset. Moreover, the Enhanced Elman Spike Neural Network (EESNN) model detects cyber-attacks. Furthermore, the Archimedes Optimization Algorithm (AOA) model is employed to select the optimum hyperparameter for the EESNN model. The empirical analysis of the ACAD-BMDL technique is performed on a benchmark dataset. The experimental validation of the ACAD-BMDL technique portrayed a superior accuracy value of 99.12% and 99.36% under NSLKDD2015 and CICIDS2017 datasets in the CPS environment.
Forests are the largest pool of carbon in terrestrial ecosystems and are important for climate change mitigation. By analyzing the carbon sequestration process of forest ecosystem, the carbon sequestration amount of f...
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In today's world, it is vital and in trend to evaluate the firewall of computer networks and control internet traffic based on the research findings. A firewall is an excellent tool that ensures traffic control du...
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The field of laser-ion acceleration faces significant challenges in handling high-dimensional, computationally intensive problems, often constrained by budgets and available computational power. Reliably achieving hig...
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The proceedings contain 72 papers. The special focus in this conference is on Production and Industrial Engineering. The topics include: A Comprehensive Overview on Additive Manufacturing processes: Materials, Applica...
ISBN:
(纸本)9789819960934
The proceedings contain 72 papers. The special focus in this conference is on Production and Industrial Engineering. The topics include: A Comprehensive Overview on Additive Manufacturing processes: Materials, Applications, and Challenges;an Overview of the Untapped Potential of Soft Robotic Arms with Integration of Machining Tools;life Cycle Assessment of Abrasive Flow Machining of 3D Printed Parts: A Comparative analysis;Modelling and Simulation of Wire DED Additive Manufacturing process;an Overview of the Recent Advances in Additive Manufacturing, and Its Scope for the Benefit of Research and Development in Commercial Vehicle Industries;design and Development of Customized Helmet for Military Personnel;additive Manufacturing and Sustainability: The Mediating Role of Supply Chain;leverage of Metal 3D Printing Technology in the Automotive Industry;digital Twins of Hybrid Additive and Subtractive Manufacturing Systems–A Review;exploring Sustainable Manufacturing: A Comprehensive Review of Literature and Practices;performance analysis of 3D Printed Impellers for Portable Vacuum Cleaner;3D Printed Electronics: Role of Materials and processes;electrochemical Micromachining: A Review on Principles, processes, and Applications;friction and Wear Characteristics of Engine Oil Through Four-Ball Tester;recent Trends in 4th Industrial Revolution for A Sustainable Future–A Review;AI control of EMG Sensor data for 3D Printed Prosthesis Hand.
The proceedings contain 73 papers. The special focus in this conference is on Electrical Engineering and Information Technologies for Rail Transportation. The topics include: Electromagnetic Wind Energy Harvester for ...
ISBN:
(纸本)9789819993185
The proceedings contain 73 papers. The special focus in this conference is on Electrical Engineering and Information Technologies for Rail Transportation. The topics include: Electromagnetic Wind Energy Harvester for Condition Monitoring System of High-Speed Train Bogies;an Exploration of Voltage-Type Rotor Magnetic Field Indirect Vector control;method to Detect Arc Across Pantograph-Catenary Structure Atop Train Based on Frequency Features of Entry Current;a Foreign Object Detection Method for Railway Overhead Lines Based on Few-Shot Learning;transformer-Aware Graph Convolution Networks for Relation Extraction of Railway Safety Risk;a Comprehensive Study on Train Operation Dynamics and Passenger Comfort Optimization;model-Driven Study of Intelligent Passenger Information System for Urban Rail Transit;research on Positioning of Permanent Magnet Maglev Trains Based on Weighted Adaptive Kalman Information Fusion;Real-Time Low-Light Image Enhancement Method for Train Driving Scene Based on Improved Zero-DCE;analysis of Dynamic Characteristics of Dropper in Catenary System;a Power Flow Optimization Method for Urban Rail Flexible Traction Power Supply System Considering Train Dwell Time;a Mechanism and data-Driven Hybrid Mechanical Model of Rotary Arm Positioning Rubber Joint;high Speed Train Bracket Arm Visualization Experiment System;design of Cabinet-Level Refrigeration System in Subway Station Communication Signal Room;active control of Pantograph Sliding Mode Under Fluctuating Wind Excitation;Time Synchronized Sensor Network with IEEE1588 for Vibration Measurement in Structural Health Monitoring of Railway System;modeling and Implementation of EMU Traction System;traffic Operation Status Research Based on Multi-source data Fusion;isochronous Deterministic Ethernet System Research;wave Propagation in the Overhead Conductor Rail System.
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