Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across various applications. The abili...
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This paper presents a set of ontologies to organize concepts, categories, properties, and relationships that are typically used by designers for characterizing sensing and actuation devices that compose a given system...
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ISBN:
(数字)9781728182865
ISBN:
(纸本)9781728182872
This paper presents a set of ontologies to organize concepts, categories, properties, and relationships that are typically used by designers for characterizing sensing and actuation devices that compose a given system architecture (SA). From the characterization of such devices, modeling can be done using the Architecture Analysis and Design Language (AADL). AADL supports modeling and analysis of functional and nonfunctional properties to evaluate quality attributes from ontology models. The paper also proposes an AADL property set that can be applied to sensors and actuators (S&A), based on previous researches with ontologies applied to sensor networks. Specific characteristics are provided to describe systems' quality attributes. This aims to be used for analyzing the designed architecture, and also its probable future evolution.
y associating active learning methodologies and digital media as a form to improve educational quality, the diversity of experimentations in engineering education has been motivating researches in many areas with poss...
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The classification of vehicles is a matter of great importance for traffic control and management, helping with traffic surveillance as well as in statistical data collection. Among the several vehicular classificatio...
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The classification of vehicles is a matter of great importance for traffic control and management, helping with traffic surveillance as well as in statistical data collection. Among the several vehicular classification techniques, the most popular uses inductive loop sensors, because they achieve high accuracy rate at low cost. This paper proposes 5 different vehicle classification models by inductive waveform analysis: KNN, SVC, Decision Tree, Random Forest, and Voting Classifier. A brief introduction to the mathematical basis of these models and the main forms of vehicle detection are also presented. The obtained results reached an accuracy of 94% and showed how inductive waveform analysis is still a valid option for vehicle classification.
The development of artificial intelligence(AI)and the mining of biomedical data complement each *** the direct use of computer vision results to analyze medical images for disease screening,to now integrating biologic...
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The development of artificial intelligence(AI)and the mining of biomedical data complement each *** the direct use of computer vision results to analyze medical images for disease screening,to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries,the boundaries of both are constantly expanding,and their connections are becoming ***,the theme of the 2024 Annual Quantitative Biology Conference is set as“Biomedical Data and AI”,and was held in Chengdu,China from July 15 to 17,2024.
By associating active learning methodologies and digital media as a form to improve educational quality, the diversity of experimentations in engineering education has been motivating researches in many areas with pos...
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By associating active learning methodologies and digital media as a form to improve educational quality, the diversity of experimentations in engineering education has been motivating researches in many areas with possibilities of increasing both students' knowledge and skills. Control engineering is an area where educational laboratories are usually costly, thus the use of virtual laboratories for remote experimentation became an interesting approach. In this work, it is presented a remote experimentation procedure for the ball and beam system, which is a nonlinear and unstable open loop process. Considering the advanced control topic, multiobjective optimization was introduced in the experiment in order to tune Proportional-Integral-Derivative (PID) controllers. Through the description of the system model, the multiobjective optimization technique, and the experiment configuration, students can simulate and test their controllers remotely in a real plant.
Without proper coordination, power conditioners within microgrids are prone to suffer from resonance phenomena due to the complex and dynamic interactions among the main grid, nonlinear loads and distributed converter...
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Without proper coordination, power conditioners within microgrids are prone to suffer from resonance phenomena due to the complex and dynamic interactions among the main grid, nonlinear loads and distributed converters. In addition to the detriment of grid-connected devices and loads, harmonic voltage resonances may also lead to microgrid instability. As a consequence, the steering of distributed power conditioners to diminish voltage distortions and suppress undesired currents has been playing a key role on enhancing the operational stiffness of microgrids. In general, such conditioners are driven by the synthesis of sinusoidal currents independently on the status of voltage waveforms, which may not adequately damp harmonic resonances and still jeopardize system stability. Thus, this work proposes the coordination of multiple parallel power conditioners, which are driven as controlled current sources, through a current-based approach that synthesizes resistive loads, enhancing the system capability to damp voltage resonances, as well as improving power quality within microgrids. Simulation results comprising a single-phase microgrid with resonant and nonlinear loads, as well as two distributed power conditioners, are presented to demonstrate the effectiveness of the approach.
The presence of distributed generation systems spread over low-voltage electrical networks is boosting the development of control methodologies aiming at coordinating and cooperatively managing the existing smart inve...
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ISBN:
(数字)9781728141800
ISBN:
(纸本)9781728141817
The presence of distributed generation systems spread over low-voltage electrical networks is boosting the development of control methodologies aiming at coordinating and cooperatively managing the existing smart inverters. Although low-bandwidth data transmission links are constantly described to be required for a considerable number of centralized and decentralized control methodologies, there is a gap in literature concerning the plain understanding of the features of the related communication protocols available for such application. Thus, this paper brings considerations on some of the most relevant communication protocols that can be applied to the cooperative control of multiple smart inverters, taking into account the recent updates on interoperability requirements recommended by the IEEE 1547-2018 standard. The communication infrastructure, topology and features of a low-bandwidth data transmission link are discussed in this paper focusing on the SunSpec, DNP3 and SEP2 protocols. Yet, some critical comments are made regarding the practical interoperability of commercial inverters, also bordering cyber security matters.
This paper proposes an additive nanomanufacturing approach to fabricate a personalized lab-on-a-chip fluorescent peptide nanoparticles （f-PNPs） array for simultaneous multi-biomarker detection that can be used in Al...
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This paper proposes an additive nanomanufacturing approach to fabricate a personalized lab-on-a-chip fluorescent peptide nanoparticles （f-PNPs） array for simultaneous multi-biomarker detection that can be used in Alzheimer＇s disease （AD） diagnosis. We will discuss optimization techniques for the additive nanomanufacturing process in terms of reliability, yield and manufacturing efficiency. One contribution of this paper lies in utilization of additive nanomanufacturing techniques to fabricate a patient-specific customize-designed lab-on-a-chip device for personalized AD diagnosis, which remains a major challenge for biomedical engineering. Through the integrated bio-design and bio-manufacturing process, doctor＇s check- up and computer-aided customized design are integrated into the lab-on-a-chip array for patient-specific AD diagnosis. In addition, f-PNPs with targeting moieties for personalized AD biomarkers will be self-assembled onto the customized lab-on-a- chip through the additive nanomanufacturing process, which has not been done before. Another contribution of this research is the personalized lab-on-a-chip f-PNPs array for AD diagnosis utilizing limited human blood. Blood-based AD assessment has been described as ＂the holy grail＂ of early AD detection. This research created the computer-aided design, fabrication through additive nanomanufacturing, and validation of the f-PNPs array for AD diagnosis. This is a highly interdisciplinary research contributing to nanotechnology, biomaterials, and biomedical engineering for neurodegenerative disease. The conceptual work is preliminary with intent to introduce novel techniques to the application. Large-scale manufacturing based on the proposed framework requires extensive validation and optimization.
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