Real Events Research Articles

“This community will grow” — little concern for future wildfires in a dry and increasingly hotter Swedish rural community

Increased risk of wildfires is often highlighted in media coverage of climate change in the Nordic countries. How an increased risk is reflected in the concerns and adaptive measures within the most likely affected communities is nevertheless not known. This study investigates concerns and adaptation to wildfires in a rural community in south-eastern Sweden. The comparatively dry study area has a history of frequent but often low-consequence wildfires and is projected to experience Sweden’s largest increase in severe fire weather towards 2100. Through narratives, this study elucidates potential wildfire concerns in this area and motivations behind adaptation measures. The narratives are compared to a physical causal network extracted from the literature on fires and their consequences in the region. Residents foresee an increased wildfire risk but do not consider it a threat to the future well-being of the community. Forest owners and homeowners express low commitment in preventive or adaptive measures. Instead, contrasting the reality of the twentieth century, the fire service is currently considered to be responsible for both preventing and suppressing fires. This attitude is attributed to the lack of severe implications from the generally well-managed fires in the region. Actions for prevention and adaptation seem triggered by media attention or experience from real high-consequence events occurring elsewhere, rather than local wildfire occurrence or climate change projections.

Automated Trace Clustering Pipeline Synthesis in Process Mining

Business processes have undergone a significant transformation with the advent of the process-oriented view in organizations. The increasing complexity of business processes and the abundance of event data have driven the development and widespread adoption of process mining techniques. However, the size and noise of event logs pose challenges that require careful analysis. The inclusion of different sets of behaviors within the same business process further complicates data representation, highlighting the continued need for innovative solutions in the evolving field of process mining. Trace clustering is emerging as a solution to improve the interpretation of underlying business processes. Trace clustering offers benefits such as mitigating the impact of outliers, providing valuable insights, reducing data dimensionality, and serving as a preprocessing step in robust pipelines. However, designing an appropriate clustering pipeline can be challenging for non-experts due to the complexity of the process and the number of steps involved. For experts, it can be time-consuming and costly, requiring careful consideration of trade-offs. To address the challenge of pipeline creation, the paper proposes a genetic programming solution for trace clustering pipeline synthesis that optimizes a multi-objective function matching clustering and process quality metrics. The solution is applied to real event logs, and the results demonstrate improved performance in downstream tasks through the identification of sub-logs.

Research on information spreading of SISIOIN model in social networks

This paper focuses on the internal law of online public opinion spreading under the conditions of different types of spreaders by constructing the model of public opinion spreading by subtypes of spreaders. The new [Formula: see text] model is constructed by abstracting factors such as netizens’ interests, emotions and views on hot events in the Internet into propensity indices. The simulation results show that the spread of public opinion after categorizing netizens is more in line with the spread of public opinion in reality. Moreover, netizens tend to show different spreading behaviors in different public opinion cases, and the degree of change in netizens’ propensity varies greatly. All the data used in the simulation experiments are real data and analyzed with real events. The research results are helpful for what kind of control strategies are adopted after the occurrence of hotspot events.

Experimental use of pig cadavers to locate homicide victim in a large river

The transport of full body human remains in fluvial environments has few published examples to guide recovery efforts. The decomposition stage, flow environment, water temperature and river morphology can all interact to affect the rate and distance deceased human bodies will travel, and case studies or experimental efforts are rare. In this case report, we provide an experimental deployment of pig carcasses to emulate a real homicide event where a body was dropped into a large 7th order Northern Great Plains river to guide recovery of the victims remains. Two pigs were deployed, one wrapped in a tarp to reflect the victim’s circumstances and the other uncovered in a time period and flow condition comparable to what was known of the homicide. The results of the transport are reported, along with the successful recovery of the victim’s remains near one of the pig cadavers. Although small in scope and un-replicated, this case study should be a valuable contribution to knowledge of full body human fluvial taphonomy in the future and help inform future search efforts of comparable systems.

Non‐Double‐Couple Components of Seismic Source: Method and Application to the 2014–2015 Bárðarbunga Volcanic Event Sequence, Iceland

AbstractGenuine non‐double‐couple (non‐DC) components of a seismic source, defined here as the non‐DC components that are not due to summation of pure double‐couple (DC) components, provide important insight into special physical processes in non‐earthquake sources such as explosion, volcano eruption and collapse etc. Yet they remain challenging to be resolved. To address the issue and explore the physical mechanism of those special events, we develop a waveform‐polarity‐based moment tensor (WPMT) inversion method and employ it to study physical process in the 2014–2015 Bárðarbunga volcano event sequence. The WPMT method incorporates P‐wave polarity data and seismic waveforms in the source inversion, designs a source simplicity test to check possible complex rupture in the seismic source, and employs a simulated annealing algorithm to search the best source solution. The simplicity test checks consistency of the source processes in the initiation stage of the event and the major energy release process of the event, thus ensuring that the inferred non‐DC components are genuine to the seismic source. Real event and synthetic tests indicate that the WPMT method can identify and resolve genuine non‐DC components in a seismic source. The WPMT inversions of the Bárðarbunga sequence yield many genuine non‐DC source components and reveal that the eruptions are accompanied by seismic activities in depths of 1–5 km with magma migrations out of chambers, collapses of conduits, failures of normal faults, and a magma recharge at a depth of 9 km accompanied by a failure on a nearby normal fault.

An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning

Coronal mass ejections (CMEs) constitute the major source of severe space weather events, with the potential to cause enormous damage to humans and spacecraft in space. It is becoming increasingly important to detect and track CMEs, since there are more and more space activities and facilities. We have developed a new algorithm to automatically derive a CME’s kinematic parameters based on machine learning. Our method consists of three steps: recognition, tracking, and the determination of parameters. First, we train a convolutional neural network to classify images from Solar and Heliospheric Observatory Large Angle Spectrometric Coronagraph observations into two categories, containing CME(s) or not. Next, we apply the principal component analysis algorithm and Otsu’s method to acquire binary-labeled CME regions. Then, we employ the track-match algorithm to track a CME’s motion in time-series images and finally determine the CME’s kinematic parameters, e.g., velocity, angular width, and central position angle. The results of four typical CME events with different morphological characteristics are presented and compared with a manual CME catalog and several automatic CME catalogs. Our algorithm shows some advantages in the recognition of CME structure and the accuracy of the kinematic parameters. This algorithm can be helpful for real-time CME warnings and predictions. In the future, this algorithm is capable of being applied to CME initialization in magnetohydrodynamic simulations to study the propagation characteristics of real CME events and to provide more efficient predictions of CMEs’ geoeffectiveness.

Enhancing Robotic Perception through Synchronized Simulation and Physical Common-Sense Reasoning.

We introduce both conceptual and empirical findings arising from the amalgamation of a robotics cognitive architecture with an embedded physics simulator, aligning with the principles outlined in the intuitive physics literature. The employed robotic cognitive architecture, named CORTEX, leverages a highly efficient distributed working memory known as deep state representation. This working memory inherently encompasses a fundamental ontology, state persistency, geometric and logical relationships among elements, and tools for reading, updating, and reasoning about its contents. Our primary objective is to investigate the hypothesis that the integration of a physics simulator into the architecture streamlines the implementation of various functionalities that would otherwise necessitate extensive coding and debugging efforts. Furthermore, we categorize these enhanced functionalities into broad types based on the nature of the problems they address. These include addressing challenges related to occlusion, model-based perception, self-calibration, scene structural stability, and human activity interpretation. To demonstrate the outcomes of our experiments, we employ CoppeliaSim as the embedded simulator and both a Kinova Gen3 robotic arm and the Open-Manipulator-P as the real-world scenarios. Synchronization is maintained between the simulator and the stream of real events. Depending on the ongoing task, numerous queries are computed, and the results are projected into the working memory. Participating agents can then leverage this information to enhance overall performance.

Моделирование оценки риска пожара на резервуаре хранения нефтепродуктов

The purpose of the study is to assess the consequences of emergency situations in real danger, it is necessary to carry out studies to determine the degree of risk of accidents in the form of fires and explosions on technological equipment for processing and storage of petroleum products. When operating oil tanks, it is recommended to use the «fault tree» method to predict failures or failures’. This method is a logical-probabilistic model of the causal relationship of a tank fire with defects in its elements and other events. This will allow you to use the modeling method to determine the probability of an event using an analytical or statistical distribution function of a random variable representing a real event. Using the «fault tree», you can calculate the probability of a «failure» event and uptime. In the article, a reliability model is constructed, which is a logical-probabilistic model of cause-and-effect relationships of a tank fire with malfunctions of its elements and other events.

A Nineteenth Century Rural Crime in Western Queensland?

In August 1895, Andrew Barton “Banjo” Paterson was visiting his fiancée at Dagworth Station near Winton in western Queensland, Australia, when he was moved to write a bush ballad that became more prominent than even he might have expected. The question arises as to what was or were the circumstances or events that stimulated the creative mind of Paterson to write such a spirited ballad. A rural crime was certainly committed down by the billabong in the ballad, but there were real events playing out throughout the western sheep grazing country of Queensland at that time and had been for some years. This research note argues that, in identifying crimes, we can observe a dichotomy of opposites with some boundaries being contained, while others are large and fluid. Each have a particular fragility as well as a strength. Contained boundaries have a placement that has strength, but vulnerability to encroachment by powerful forces: the need to protect is ever present. It is also argued that this ballad, which contextualises a rural crime, serves as an allegory symbolising a sense of injustice, of resistance against injustice and excessive use of power.

Social Media and Social Networking

A Social networking service (also social networking site, SNS or social media) is an online platform that is used by people to build social networks or social relations with other people who share similar personal or career interests, activities, backgrounds or real-life connections. The variety of stand-alone and built-in social networking services currently available in the online space introduces challenges of definition; however, there are some common features: (1) social networking services are Web 2.0 internet-based applications, (2) user-generated content (UGC) is the lifeblood of SNS organisms, (3) users create service-specific profiles for the site or app that are designed and maintained by the SNS organization, and (4) social networking services facilitate the development of online social networks by connecting a user's profile with those of other individuals and/or groups. Most social network services are web-based and provide means for users to interact over the Internet, such as by e-mail and instant messaging and online forums. Social networking sites are varied and they incorporate a range of new information and communication tools such as availability on desktop and laptops, mobile devices such as tablet computers and smart phones, digital photo/video/sharing and "web logging" diary entries online (blogging). Online community services are sometimes considered a social network service, though in a broader sense, social network service usually means an individual-centered service whereas online community services are group-centered. Social networking sites allow users to share ideas, digital photos and videos, posts, and inform others about online or real world activities and events with people in their network. While in-person social networking, such as gathering in a village market to talk about events has existed since the earliest developments of towns, the Web enables people to connect with others who live in different locations, ranging from across a city to across the world. Depending on the social media platform, members may be able to contact any other member. Key words : Social Networking, e-mail, Web-based, Social Media, Face Book .

Scaling Toward Utopia or Dystopia: Challenges to Preserving Organizational Values Through Growth

In their nascent stages, charter schools formed under competing ideologies. In academic circles, charter schools were envisioned as pedagogical laboratories that would allow for educator- and community-driven school improvement. In other circles, charter schools emerged as a free-market reform driven by accountability, choice, and growth. Amid the neoliberal accountability era, the latter ideology has emerged as a stronger driving force across the educational landscape, particularly amid the proliferation of Charter Management Organizations (CMOs). Based on real events, a charter school founder struggles to hold onto organizational values while scaling from a small charter school to a large CMO.

A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs

Continuously observed event occurrences, often exhibit self and mutually exciting effects, which can be well modeled using temporal point processes. Beyond that, these event dynamics may also change over time, with certain periodic trends. We propose a novel variational autoencoder to capture such a mixture of temporal dynamics. More specifically, the whole time interval of the input sequence is partitioned into a set of sub intervals. The event dynamics are assumed to be stationary within each subinterval, but could be changing across those subintervals. In particular, we use a sequential latent variable model to learn a dependency graph between the observed dimensions, for each subinterval. The model predicts the future event times, by using the learned dependency graph to remove the non contributing influences of past events. By doing so, the proposed model demonstrates its higher accuracy in predicting inter event times and event types for several real world event sequences, compared with existing state of the art neural point processes.

E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning

The bio-inspired event cameras or dynamic vision sensors are capable of asynchronously capturing per-pixel brightness changes (called event-streams) in high temporal resolution and high dynamic range. However, the non-structural spatial-temporal event-streams make it challenging for providing intuitive visualization with rich semantic information for human vision. It calls for events-to-video (E2V) solutions which take event-streams as input and generate high quality video frames for intuitive visualization. However, current solutions are predominantly data-driven without considering the prior knowledge of the underlying statistics relating event-streams and video frames. It highly relies on the non-linearity and generalization capability of the deep neural networks, thus, is struggling on reconstructing detailed textures when the scenes are complex. In this work, we propose E2HQV, a novel E2V paradigm designed to produce high-quality video frames from events. This approach leverages a model-aided deep learning framework, underpinned by a theory-inspired E2V model, which is meticulously derived from the fundamental imaging principles of event cameras. To deal with the issue of state-reset in the recurrent components of E2HQV, we also design a temporal shift embedding module to further improve the quality of the video frames. Comprehensive evaluations on the real world event camera datasets validate our approach, with E2HQV, notably outperforming state-of-the-art approaches, e.g., surpassing the second best by over 40% for some evaluation metrics.

Positioning of facts, meanings and terms in the media: theoretical approaches and practice of covering the problems of terrorism

The interpretation and interrelation of the concepts of “fact”, “meaning”, “term” throughout the 20th–21st centuries were constantly in the zone of interest of researchers: sociologists, philosophers, cultural scientists, linguists, lawyers, as well as writers and journalists. At the same time, this connection, outwardly understandable and logical, was understood as an increasingly complex composition, depending both on the peculiarities of human perception and on the social modeling of various kinds of messages to target audiences. This article examines the dynamics and current state of these ideas, connected, on the one hand, with the internetization and mediatization of society; and, on the other, motivated by the presence and strengthening of the global socio-political conjuncture at the interstate and other levels. The author’s research focuses on the problems of terrorism as the most acute and revealing. There is no unified internationally accepted definition of terrorism. To an even greater extent, this applies to social practice, in the process of which the perpetrators and customers of terrorist attacks are determined by interested parties in different ways, up to the complete opposite. The immediate facts of terror are interpreted in the same way, when the fixation of a real event is supplemented or completely replaced by a demonstration of its meaning. The article examines the prerequisites and modern practice of creating and subsequent application of factual, meaning and terms elements in the compositions of published messages. By analyzing the materials of Russian and Western mass media, the author explores the dynamic change in the goals and roles of these elements in influencing target audiences. In the course of the study, the hypothesis is put forward and confirmed that reports of acts of terror turn into an instrument of information warfare, and their semantic part acquires a dominant character. Technologies are being developed to verify the facts for authenticity and identify the primary goals of the authors of the messages. However, the priority form of counter-actions is the formation of stereotypical attitudes among target groups to the rejection of events, statements and their content designations in the media, qualified by the state as terrorist.

The Visions of a Visionary—Girish Karnard’s Play The Dreams of Tipu Sultan

Indian playwright Girish Karnad seeks to challenge the conventional historical portrayal of Tipu Sultan in his play Dreams of Tipu Sultan by emphasizing Tipu’s personal and psychological experiences. As a pioneering playwright known for blending diverse theatrical styles, Karnad integrates real historical events with creative storytelling to present Tipu Sultan as a complex figure deserving of both respect and empathy. The play begins not with the central character of Tipu Sultan, but with two historians, Mysorian Kirmani and the British Colin Mackenzie. These historians serve as a lens through which the audience can explore and question the traditional narratives surrounding Tipu Sultan’s life and reign. They raise important inquiries about the authenticity of historical accounts and traditional narratives and encourage a more nuanced understanding of Tipu Sultan’s motivations, relationships, and inner world. By delving into the personal and psychological experiences of Tipu Sultan, Karnad invites us to question and reevaluate our understanding of history, new historicism, and the human portrayal of the historical figure Tipu Sultan.

Impact of spy fiction on cognition: a case study

Reading spy fiction has imprinted its traces on the thinking patterns of the readers that encourage them to consider it as a real event in their life. This case study is about a 37 year old woman, referred by a senior clinical psychologist with complaints of having the feeling of being monitored through a device and hearing the voices of the people. The brief therapeutic plan was based on Cognitive Behavioural Therapy which focused on developing insight, identifying cognitive errors, and enhancing her socialisation skills. This case report holds its implications to drift the attention of the readers and clinicians toward the issue of consuming content that may potentially have an impact on its reader’s mental health.

Grid Forming Technologies to Improve Rate of Change in Frequency and Frequency Nadir: Analysis-Based Replicated Load Shedding Events

Electric power generation is quickly transitioning toward nontraditional inverter-based resources (IBRs). Prevalent devices today are solar PV, wind generators, and battery energy storage systems (BESS) based on electrochemical packs. These IBRs are interconnected throughout the power system via power electronics inverter bridges, which have sophisticated controls. This paper studies the impacts and benefits resulting from the integration of grid forming (GFM) inverters and energy storage on the stability of power systems via replicating real events of loss of generation units that resulted in large load shedding events. First, the authors tuned the power system dynamic model in Power System Simulator for Engineering (PSSE) to replicate the event records and, upon integrating the IBRs, analyzed the system dynamic responses of the BESS. This was conducted for both GFM and grid following (GFL) modes. Additionally, models for Grid Forming Static Synchronous Compensator (GFM STATCOM), were also created and simulated to allow for quantifying the benefits of this technology and a techno-economic analysis compared with GFM BESSs. The results presented in this paper demonstrate the need for industry standardization in the application of GFM inverters to unleash their benefits to the bulk electric grid. The results also demonstrate that the GFM STATCOM is a very capable system that can augment the bulk system inertia, effectively reducing the occurrence of load shedding events.

Regional development of Kazakhstan: Theoretical premises and reality

The present study examines the issues of regional development of Kazakhstan in the context of history and real events. The relevance of the study is due to the need to search and adapt the accumulated advanced experience in regional development as a part of smoothing the differentiation of territories in the socio‐economic sphere and the search for effective methods of managing them. The purpose of the study is to search for and identify an effective theoretical model of regional development of the Republic of Kazakhstan that meets the urgent needs for the rational use of the resources available, which is a prerequisite for future economic development, and, as a result, improves the quality of life in the regions. The leading approach in this paper is a combination of analytical and information‐logical methods to determine the existing historical prerequisites and real grounds for the theoretical substantiation of the stages of regional development in Kazakhstan. The results of this study emphasize the need to objectively take into account the peculiarities of the development of the region and its actual state.

GENRE FEATURES OF MODERN NON-FICTION LITERATURE (ON THE EXAMPLE OF THE BOOK "DREAM OF ANTARCTIC" BY MARKIYAN PROKHASKO)

The end of the 20th – the beginning of the 21st century is characterized by the fact that during this period, interest in non-fiction literature – a special literary genre of documentary prose, which is based on real events, without fiction or conjecture – begins to grow actively. Facts are presented through the imaginative perception of the world by the author of the work. Therefore, in our opinion, this genre can still be called “documentary journalism of life”. Non-fiction has gained particular popularity over the past few years. This is connected, first of all, with the events that are taking place, namely: with the full-scale invasion of the Russian Federation on the territory of Ukraine. Collections of books about the war, the Maidan, and the Revolution of Dignity are published, as well as books that have become bestsellers in the world of psychology, travel journalism, and literature. The article examines the issue of genre features of the book “Dream of Antarctica”, which is an example of modern non-fiction literature. It is clarified why the diffusion of genres is a part of the analyzed book, and how the author combines features of other genres in one work.

Explaining the GWSkyNet-Multi Machine Learning Classifier Predictions for Gravitational-wave Events

GWSkyNet-Multi is a machine learning model developed for the classification of candidate gravitational-wave events detected by the LIGO and Virgo observatories. The model uses limited information released in the low-latency Open Public Alerts to produce prediction scores indicating whether an event is a merger of two black holes (BHs), a merger involving a neutron star (NS), or a non-astrophysical glitch. This facilitates time-sensitive decisions about whether to perform electromagnetic follow-up of candidate events during LIGO-Virgo-KAGRA (LVK) observing runs. However, it is not well understood how the model is leveraging the limited information available to make its predictions. As a deep learning neural network, the inner workings of the model can be difficult to interpret, impacting our trust in its validity and robustness. We tackle this issue by systematically perturbing the model and its inputs to explain what underlying features and correlations it has learned for distinguishing the sources. We show that the localization area of the 2D sky maps and the computed coherence versus incoherence Bayes factors are used as strong predictors for distinguishing between real events and glitches. The estimated distance to the source is further used to discriminate between binary BH mergers and mergers involving NSs. We leverage these findings to show that events misclassified by GWSkyNet-Multi in LVK’s third observing run have distinct sky areas, coherence factors, and distance values that influence the predictions and explain these misclassifications. The results help identify the model’s limitations and inform potential avenues for further optimization.