Knowledge Modeling of power grid regulation based on reasoning map

To contribute to the intelligence and knowledge of power grid regulation and control operations, this paper presents a method of power grid regulation knowledge modeling based on ELG (Event Logic Graph), which includes an event word extraction based on a predicate-argument model, an event chain extraction and fusion based on event similarity theory, an event generalization based on a soft-pattern algorithm, and an event relationship recognition based on rule pattern matching method and joint constraints. Finally, this paper uses events as nodes and event relationships as directed edges to construct an affair graph stipulated by the power grid regulation and control regulations. The ELG is also called the new generation knowledge graph. But the knowledge graph can only describe the existence of entities and the upper and lower associations between entities. ELG can explain the inheritance, causality between entities and the logic of affair evolution, and the probability of transition between legacy and causality. Therefore, knowledge modeling based on ELG has intelligent advantages. Also, compared with ontology-based knowledge modeling methods, the method proposed in this paper can realize the dynamic representation of control operation knowledge, can express the logic of behavior and logic of operation, and also has higher retrieval accuracy.

Multi-Response Awareness for Retrieval-Based Conversations: Respond with Diversity via Dynamic Representation Learning

Conversational systems now attract great attention due to their promising potential and commercial values. To build a conversational system with moderate intelligence is challenging and requires big (conversational) data, as well as interdisciplinary techniques. Thanks to the prosperity of the Web, the massive data available greatly facilitate data-driven methods such as deep learning for human-computer conversational systems. In general, retrieval-based conversational systems apply various matching schema between query utterances and responses, but the classic retrieval paradigm suffers from prominent weakness for conversations: the system finds similar responses given a particular query. For real human-to-human conversations, on the contrary, responses can be greatly different yet all are possibly appropriate. The observation reveals the diversity phenomenon in conversations. In this article, we ascribe the lack of conversational diversity to the reason that the query utterances are statically modeled regardless of candidate responses through traditional methods. To this end, we propose a dynamic representation learning strategy that models the query utterances and different response candidates in an interactive way. To be more specific, we propose a Respond-with-Diversity model augmented by the memory module interacting with both the query utterances and multiple candidate responses. Hence, we obtain dynamic representations for the input queries conditioned on different response candidates. We frame the model as an end-to-end learnable neural network. In the experiments, we demonstrate the effectiveness of the proposed model by achieving a good appropriateness score and much better diversity in retrieval-based conversations between humans and computers.

Distinct Representations of Body and Head motion are Dynamically Encoded by Purkinje cell Populations in the Macaque Cerebellum

The ability to accurately control our posture and perceive spatial orientation during self-motion requires knowledge of the motion of both the head and body. However, whereas the vestibular sensors and nuclei directly encode head motion, no sensors directly encode body motion. Instead, the integration of vestibular and neck proprioceptive inputs is necessary to transform vestibular information into the body-centric reference frame required for postural control. The anterior vermis of the cerebellum is thought to play a key role in this transformation, yet how its Purkinje cells integrate these inputs or what information they dynamically encode during self-motion remains unknown. Here we recorded the activity of individual anterior vermis Purkinje cells in alert monkeys during passively applied whole-body, body-under-head, and head-on-body rotations. Most neurons dynamically encoded an intermediate representation of self-motion between head and body motion. Notably, these neurons responded to both vestibular and neck proprioceptive stimulation and showed considerable heterogeneity in their response dynamics. Furthermore, their vestibular responses demonstrated tuning in response to changes in head-on-body position. In contrast, a small remaining percentage of neurons sensitive only to vestibular stimulation unambiguously encoded head-in-space motion across conditions. Using a simple population model, we establish that combining responses from 40 Purkinje cells can explain the responses of their target neurons in deep cerebellar nuclei across all self-motion conditions. We propose that the observed heterogeneity in Purkinje cells underlies the cerebellum's capacity to compute the dynamic representation of body motion required to ensure accurate postural control and perceptual stability in our daily lives.

Analysis of the dynamic effect of the electrical interconnection on the stability of the rotor angle for synchronous generators in the electric power system of Syria

This article focuses on the study and analysis of the importance of interconnections between electricity systems, which increases with greater probability due to the dependence of all countries and States on electricity and the ease of its transfer between countries in order to supplement their economic and technical benefits. THE PURPOSE. This study analyzes the dynamic impact of interconnection on circuit stability for synchronous generators in Syrian power grids. In addition, the authors of the article analyzed the dynamic effect of interaction on the stability of the angle of rotation of the rotor of synchronous generators operated in the Syrian power system through the use of dynamic modeling of the country's power system. METHODS. In the course of the study, the authors used a technique based on the dynamic representation of the power system and the construction of its nonlinear equations, followed by the use of the PSS ® E program. 230-400 kV.RESULTS. The authors of the article obtained a solution and determination of the system parameters and the separation time of the boundaries of three-phase short circuits in a 400 kV network in addition to determining the angular position of the generator circuits, and thus, its stability was checked, regardless of whether it works independently in the electric power system of Syria or is part of a network. CONCLUSION. In the course of the study, the authors obtained the following conclusions, such as: an increase in CFCT was found for generating units in the power system of Syria due to connection activation, an increase in transmitted power, which leads to an increase in the stabilization zone after a failure and before the start of connecting electrical systems to the country's power system, as well as it is necessary to conduct in-depth dynamic studies of the entire system in order to represent the effect of the connection on the parameters of the system, taking into account the increase in power.

Using Rich Narratives to Engage Students in Worthwhile Mathematics: Children’s Literature, Movies and Short Films

Using children’s literature to support mathematics instruction has been connected to positive academic outcomes and learning dispositions; however, less is known about the use of audiovisual based narrative mediums to support student mathematical learning experiences. The current exploratory, qualitative study involved teaching three lessons based on challenging, problem solving tasks to two classes of Australian Year (Grade) 5 students (10 and 11 year olds). These tasks were developed from various narratives, each portrayed through a different medium (movie clip, short film, picture story book). Post lesson interviews were undertaken with 24 students inviting them to compare and contrast this lesson sequence with their usual mathematics instruction. Drawing on a self-determination theory lens, our analysis revealed that these lessons were experienced by students as both highly enjoyable and mathematically challenging. More specifically, it was found that presenting mathematics tasks based on rich and familiar contexts and providing meaningful choices about how to approach their mathematical work supported student autonomy. In addition, there was evidence that the narrative presentation supported student understanding of the mathematics through making the tasks clearer and more accessible, whilst the audiovisual mediums (movie clip, short film) in particular provided a dynamic representation of key mathematical ideas (e.g., transformation and scale). Students indicated an eclectic range of preferences in terms of their preferred narrative mediums for exploring mathematical ideas. Our findings support the conclusion that educators and researchers focused on the benefits of teaching mathematics through picture story books consider extending their definition of narrative to encompass other mediums, such as movie clips and short films.

The continuous and changing impact of affect on risky decision-making

Affective experience has an important role in decision-making with recent theories suggesting a modulatory role of affect in ongoing subjective value computations. However, it is unclear how varying expectations and uncertainty dynamically influence affective experience and how dynamic representation of affect modulates risky choices. Using hierarchical Bayesian modeling on data from a risky choice task (N = 101), we find that the temporal integration of recently encountered choice parameters (expected value, uncertainty, and prediction errors) shapes affective experience and impacts subsequent choice behavior. Specifically, experienced arousal prior to choice was associated with increased loss aversion, risk aversion, and choice consistency. Taken together, these findings provide clear behavioral evidence for continuous affective modulation of subjective value computations during risky decision-making.

Dynamic representation of space in the hippocampus: spatial novelty detection and consolidation in CA1 and CA2

Hippocampal place cells are the functional units of spatial navigation and are present in all subregions- CA1, CA2, CA3 and CA4. Recent studies on CA2 have indicated its role in social and contextual memory, but its contribution towards spatial novelty detection and consolidation remains largely unknown. The current study aims to uncover how CA1 and CA2 detect, process, assimilate and consolidate spatial novelty. Accordingly, a novel 3-day paradigm was designed where the animal was introduced to a completely new environment on the first day and to varying degrees of familiarity and novelty on subsequent days, as the track was extended in length and modified in shape, keeping other environmental constraints fixed. Detection of spatial novelty was found to be a dynamic and complex phenomenon, characterized by different responses from hippocampal place cells, depending on when novelty was introduced. Therefore, the study concludes that early novelty detection (the first time a novel space is introduced in a relatively familiar environment) and subsequent novelty detection are not processed in the same way. Additionally, while neuronal responses to spatial novelty detection (early and subsequent) were found to be the same in CA1 and CA2 ensembles, their responses differed in spatial consolidation mechanisms during subsequent sleep replays. For CA1, spatial coverage of prior behaviour was found to be closely reflected in subsequent sleep for that particular day, but CA2 showed no such coherent response, highlighting mnemonic processing differences between CA2 and CA1 with respect to spatial novelty.