1. Power-based concept for current injection by inverter-interfaced distributed generations during transmission-network faultsBoštjan Polajžer, Bojan Grčar, Jernej Černelič, Jožef Ritonja, 2021, original scientific article Abstract: This paper analyzes the influence of inverter-interfaced distributed generations’ (IIDGs)
response during transmission network faults. The simplest and safest solution is to switch IIDGs
off during network faults without impacting the network voltages. A more elaborate and efficient
concept, required by national grid codes, is based on controlling the IIDGs’ currents, involving
positive- and negative-sequence voltage measured at the connection point. In this way the magnitude
and phase of the injected currents can be adjusted, although the generated power will depend on the
actual line voltages at the connection point. Therefore, an improved concept is proposed to adjust
IIDGs’ fault current injection through the required active and reactive power, employing the same
voltage characteristics. The proposed, i.e., power-based concept, is more definite than the currentbased one, since the required power will always be generated. The discussed concepts for the fault
current injection by IIDGs were tested in different 110-kV networks with loop and radial topologies,
and for different short-circuit capabilities of the aggregated network supply. Based on extensive
numerical calculations, the power-based concept during transmission networks faults generates
more reactive power compared to the current-based concept. However, the voltage support by IIDGs
during transmission networks faults, regardless of the concept being used, is influenced mainly
by the short-circuit capability of the aggregated network supply. As regards distance protection
operation, it is influenced additionally by the network topology, i.e., in radial network topology, the
remote relay’s operation can be delayed due to a largely seen impedance.
Keywords: distributed generation, fault current injection, voltage support, distance protection, transmission network faults
Published in DKUM: 16.06.2025; Views: 0; Downloads: 0
 Full text (1,39 MB)
This document has many files! More... |
2. Predicting the probability of cargo theft for individual cases in railway transportLorenc Augustyn, Małgorzata Kuźnar, Tone Lerher, Maciej Szkoda, 2020, original scientific article Abstract: In the heavy industry, the value of cargo transported by rail is very high. Due to high value, poor security and volume of rail transport, the theft cases are often. The main problem of securing rail transport is predicting the location of a high probability of risk. Because of this,the aim of the presented research was to predict the highest probability of rail cargo theft for areas. It is important to prevent theft cases by better securing the railway lines. To solve that problem the authors' model was developed. The model uses information about past transport cases for the learning process of Artificial Neural Networks (ANN) and Machine Learning (ML).The ANN predicted the probability for 94.7% of the cases of theft and the Machine Learning identified 100% of the cases. This method can be used to develop a support system for securing the rail infrastructure.
Keywords: rail transport security, supply chain disruption, drones, security support systems, cargo theft, predicting, logistics, artificial neural network, drone monitoring, machine learning
Published in DKUM: 28.01.2025; Views: 0; Downloads: 4
Full text (1,93 MB)
This document has many files! More... |
3. Social reappraisal of emotions is linked with the social presence effect in the default mode networkXiyao Xie, Teresa Bertram, Saša Zorjan, Marina Horvat, Christian Sorg, Satja Mulej Bratec, 2023, original scientific article Abstract: Introduction: Social reappraisal, during which one person deliberately tries to regulate another’s emotions, is a powerful cognitive form of social emotion regulation, crucial for both daily life and psychotherapy. The neural underpinnings of social reappraisal include activity in the default mode network (DMN), but it is unclear how social processes influence the DMN and thereby social reappraisal functioning. We tested whether the mere presence of a supportive social regulator had an effect on the DMN during rest, and whether this effect in the DMN was linked with social reappraisal-related neural activations and effectiveness during negative emotions.
Methods: A two-part fMRI experiment was performed, with a psychotherapist as the social regulator, involving two resting state (social, non-social) and two task-related (social reappraisal, social no-reappraisal) conditions.
Results: The psychotherapist’s presence enhanced intrinsic functional connectivity of the dorsal anterior cingulate (dACC) within the anterior medial DMN, with the effect positively related to participants’ trust in psychotherapists. Secondly, the social presence-induced change in the dACC was related with (a) the social reappraisal-related activation in the bilateral dorsomedial/dorsolateral prefrontal cortex and the right temporoparietal junction and (b) social reappraisal success, with the latter relationship moderated by trust in psychotherapists.
Conclusion: Results demonstrate that a psychotherapist’s supportive presence can change anterior medial DMN’s intrinsic connectivity even in the absence of stimuli and that this DMN change during rest is linked with social reappraisal functioning during negative emotions. Data suggest that trust-dependent social presence effects on DMN states are relevant for social reappraisal—an idea important for daily-life and psychotherapy-related emotion regulation.
Keywords: social reappraisal, social support, social emotion regulation, social presence, default mode network, interpersonal trust, anterior cingulate
Published in DKUM: 18.04.2024; Views: 357; Downloads: 254
Full text (3,54 MB)
This document has many files! More... |
