作者：
Podbucki, KacperMarciniak, TomaszPoznan University of Technology
Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawla II 24 Poznań60-965 Poland
Measuring luminous intensity using electronic sensors requires their precise positioning. In the case of mobile measurement platforms, it is important to detect the light source and thus determine the correct directio...
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electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** r...
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electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** results show that the tree initiation voltage of EP decreases,while the growth rate and the expansion coefficient increase with ***,the bubble phenomenon at high frequencies in EP composites is *** with trap distribution character-istics within the material,the intrinsic mechanism of epoxy composites to inhibit the growth of the electrical tree at different frequencies is *** can be concluded that more deep traps and blocking effect are introduced by doping nano-MgO into EP bulks,which can improve the electrical tree resistance performance of EP composites in a wide frequency range.
System identification, as a rich and vital discipline, provides a practical and general methodology and tool for quantitatively modelling the input-output relationships of dynamical systems. Sparse nonlinear system id...
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The multidimensional signed Friedkin-Johnsen (SFJ) model introduced in this paper describes opinion dynamics on a signed network in which the agents hold opinions on multiple interconnected topics and are allowed to b...
This paper presents an optimisation method for the direct energy exchange between two electric vehicle (EV) charging stations located in the UK. Each EV charging station consists of solar panels, hydrogen and battery ...
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Emergencies associated with incorrect operation of relay protection and automation (RPA) devices due to saturation of current transformers (CTs) can lead to great economic damage. The article presents an analysis of r...
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With the new feature MATLAB Compiler™ available starting R2020b Matlab, an application developed in Matlab can be packaged as docker standalone application and deployed using Docker® container service. The target...
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Robots for automated assembly are being progressively implemented in the aerospace manufacturing sector. The dim and complex internal structure of the aircrafts significantly complicates the operation of robotic arms ...
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As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around...
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As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors
Fault diagnosis of rotating machinery driven by induction motors has received increasing attention. Current diagnostic methods, which can be performed on existing inverters or current transformers of three-phase induc...
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