Single-event effects (SEEs) in a 650-V state-of-the-art SiC double-trench MOSFET (DT-MOS) are investigated using the Sentaurus TCAD tools. The safe operation areas (SOAs) for single-event burnout ...(SEB) and single-event gate rupture (SEGR) are extracted when heavy ions with different linear energy transfer (LET) impact the sensitive regions of the device. The results show that the radiation performance of the SiC DT-MOS is poor because of the very low threshold voltages of failures at a high LET range. Moreover, hardening measures, such as introducing a buffer layer and adjusting the mesa width, are discussed to assess their versatility. It is demonstrated that in contrast, the SEGR problem is more severe due to the intrinsic properties of SiC devices. Therefore, it becomes a crucial issue to find ways more suitable for the SiC DT-MOS to avoid gate oxide pre-breakdown, before they could serve as a replacement of Si counterparts in space applications.
Motivated by the risen linkage between events and Bitcoin return, this paper first defines Bitcoin-related events (BREs) based on the change points analysis and then divides these events into two ...categories. Furthermore, we model the impact of BREs on the Bitcoin market activities, using an event study methodology and a GARCH-X model. Empirical results show that the shock directions of Bitcoin-related events on Bitcoin price are heavily correlative with types of events. Additionally, there is a significant positive influence of domestic events on reaction volatility, whereas the foreign events impose their influences on both the expectations of market reactions and volatility.
•This paper firstly identifies the Bitcoin-related events based on the change points analysis and divided these events into two categories.•We further explore the Bitcoin price reactions to Bitcoin-related events.•Bitcoin-related events, views as a real change of Bitcoin return, are very frequent in the year 2013 or 2017.•The shock directions of Bitcoin-related events on Bitcoin price are heavily correlative with types of events.•The role of Bitcoin-related events information in influencing market reactions are significant and heterogeneous.
This article describes how events that make up text stories can be represented and extracted. We also address the results from our simple experiment on extracting and clustering events in terms of ...emotions, under the assumption that different emotional events can be associated with the classified clusters. Each emotion cluster is based on Plutchik’s eight basic emotion model, and the attributes of the NLTK-VADER are used for the classification criterion. While comparisons of the results with human raters show less accuracy for certain emotion types, emotion types such as joy and sadness show relatively high accuracy. The evaluation results with NRC Word Emotion Association Lexicon (aka EmoLex) show high accuracy values (more than 90% accuracy in anger, disgust, fear, and surprise), though precision and recall values are relatively low.
This study contributes to the extant literature on the leveraging of event portfolios, by applying the Model of Event Portfolio Tourism Leverage to a case study of the Volvo Ocean Race in Cardiff, ...UK. Through an examination of the various components of the model, the research demonstrates
the value of the strategies and tactics it proposes, including the amplification of visitor numbers, diversification of tourism offerings, extension of the tourism season, fostering of event tourism networks, consolidation of destination assets, and bolstering of destination authenticity.
Empirical data collected from three separate surveys, strategy documents, and feedback from stakeholders are analyzed to support this argument. The study also acknowledges some challenges to strategic portfolio management, particularly due to the fragmented nature of events suppliers in destinations
and the difficulty in assessing the impact of leveraging actions, in the absence of benchmark data related to event visitors.
This conceptual article argues for a broader view of the role of events in social systems. When analyzed as social phenomena, events can be seen as social actors that have the potential to both ...sustain and transform social systems. The maintenance of social systems is often reliant
on iterative events, regularly occurring celebrations that tend to confirm social structures. In contrast, pulsar events have the potential to transform social structures. In this sense events can be seen as actors that have important influences on social systems, particularly in linking localized
small world networks with the global space of flows. These ideas are explored through the case of Barcelona, which illustrates the interplay between these different types of events in their total portfolio, and how the extension of ritual in the sense of Collins can also contribute to the
generation of new relationships and practices in the contemporary network society. Barcelona is examined as an eventful city in which the alternation of continuity through iterative events and change through pulsar events contributes to increasing the network effects of events.
Recently, research on event management has redrawn much attention and made great progress. As the core tasks of event management, event modeling and mining are essential for accessing and utilizing ...events effectively. In this survey, we provide a detailed review of event modeling and event mining. Based on a general definition, different characteristics of events are described, along with the associated challenges. Then, we define four forms of events in order to better classify currently available but somewhat confusing event types; we also compare different event representation and relationship analysis techniques used for different forms of events. Finally, we discuss several pending issues and application-specific challenges which also shed light on future research directions.
Phasor Measurement Units (PMUs) are located at different geographic positions in the transmission system, generating measurement data that can be analyzed to monitor and control the power grid. One ...utilization for such measurement data is monitoring based on machine learning based event analysis in the transmission system, which includes event detection, localization, and classification . The approach developed in this work exploits the latent spatial and temporal features of PMU measurement data for event analysis. (1) For event detection, this research proposes a novel unsupervised "Spatial Temporal Graph Encoder Decoder" (STGED) deep learning model that concurrently/jointly exploits the spatial and temporal features of PMU measurements. STGED further supports downstream unsupervised event localization and classification. (2) For event localization, events are localized by estimating Turbulence and Proximity statistical scores over predicted measurements/output from STGED. (3) For event classification, an unsupervised algorithm is developed with a classification scoring metric that leverages physics informed rules based on the fundamentals of power system. The proposed approach is evaluated on the IEEE test systems and other benchmark systems for diversified event scenarios. Additionally, performance of the developed approach has been compared with other techniques, and validated using real-world industry data. Experimental results show that the proposed approach outperforms other existing techniques for event analysis.
A discrete event system is said to be critically observable if the observer can always determine whether the current state necessarily belongs to a set of critical states. This paper focuses on two ...issues related to the safety and security of discrete event systems, namely critical observability verification and enforcement of labeled Petri nets. First, given a bounded net, we verify its critical observability by using basis markings and solving some integer linear programming problems, thus avoiding the enumeration of the full state space of a net system. Moreover, for a non-critically observable net system, we obtain a feasible stop-free event set from a twin basis reachability graph such that a valid control policy can be always found, if the feasible stop-free event set is non-empty. Finally, according to the feasible stop-free event set, a set of disabled edges is generated, and an online control policy is developed based on the supervisory control theory, which guarantees that the closed-loop system is critically observable and deadlock-free.
Based on the simulated temperature and precipitation from CMIP6 models, the joint distribution characteristics of summer temperature and precipitation in China are described in the Copula approach. ...The occurrence risk of compound extremes (i.e., warm/dry, and warm/wet events) and corresponding univariate events (i.e., warm, wet, and dry events) in historical period are compared; and the risk changes of compound extremes are discussed under global warming 1.5 °C and 2 °C. Results show that: 1) the Copula approach can describe the joint probability distribution of summer temperature and precipitation in observation and model simulations in most parts of China except for the Qinghai-Tibet Plateau; 2) The average risk of warm and wet events in China increases by 2.3 and 1.16 times under 1.5 °C warming respectively, increases by 2.83 and 1.29 times under 2 °C warming respectively while the risk of dry events decreases in most parts of China; 3) The average of warm/wet events in China increases by 5.48 and 10.01 times under 1.5 °C and 2 °C warming, respectively. Regions over Northern China and South China experience the most increased risk about more than 8 times. The warm/dry events show less increase magnitude with 1.82 and 2.04 times under two warming climates, respectively. The highest increase in risk is mainly located in Northern China. At an additional 0.5 °C warming from 1.5 °C to 2 °C, the regional average risk of warm/dry and warm/wet events increases by 1.40 and 2.74 times, respectively. In most areas, the risk of warm/wet events increases significantly and are greater than that of warm/dry events. This indicates that controlling global warming up to 1.5 °C can avoid more intense warm/dry and warm/wet events. Our work highlights that the risk of compound extremes may be underestimated if we only consider the univariate events.
•The risk of warm/wet and warm/dry events in China increases under 1.5 °C and 2 °C warming based on the CMIP6 models.•The average of warm/wet events in China increases by 5.48 and 10.01 times under 1.5 °C and 2 °C warming, respectively.•The warm/dry events show less increase magnitude with 1.82 and 2.04 times under 1.5 °C and 2 °C warming, respectively.
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