Pooling plays an important role in generating a discriminative video representation. In this paper, we propose a new semantic pooling approach for challenging event analysis tasks (e.g., event ...detection, recognition, and recounting) in long untrimmed Internet videos, especially when only a few shots/segments are relevant to the event of interest while many other shots are irrelevant or even misleading. The commonly adopted pooling strategies aggregate the shots indifferently in one way or another, resulting in a great loss of information. Instead, in this work we first define a novel notion of semantic saliency that assesses the relevance of each shot with the event of interest. We then prioritize the shots according to their saliency scores since shots that are semantically more salient are expected to contribute more to the final event analysis. Next, we propose a new isotonic regularizer that is able to exploit the constructed semantic ordering information. The resulting nearly-isotonic support vector machine classifier exhibits higher discriminative power in event analysis tasks. Computationally, we develop an efficient implementation using the proximal gradient algorithm, and we prove new and closed-form proximal steps. We conduct extensive experiments on three real-world video datasets and achieve promising improvements.
The evolution and development of breaking news events usually present regular patterns, leading to the happening of sequential events. Therefore, the analysis of such evolutionary patterns among ...events and prediction to breaking news events from free text is a valuable capability for decision support systems. Traditional systems tend to focus on contents distribution information but ignore the inherent regularity of evolutionary events. We introduce evolutionary event ontology knowledge (EEOK) structuring the evolutionary patterns in five different event domains, namely Explosion, Conflagration, Geological Hazard, Traffic Accident, Personal Injury. Based on EEOK which provides a representing general-purpose ontology knowledge, we also explore a framework with a pipeline semantic analysis procedure of event extraction, evolutionary event recognition, and event prediction. Since the evolutionary event under each event domain has different evolution patterns, our proposed event prediction model combines the event types to capture the inherent regulation of evolutionary events. Comparative analyses are presented to show the effectiveness of the proposed prediction model compared to other alternative methods.
•We build EEOK that leverages the evolutionary event knowledge represented in standard ontology language OWL for representing a set of evolutionary patterns.•We propose a framework with a pipeline procedure from event extraction to event prediction.•Considering the different event domains, we offer a domain-aware event prediction method which has been shown superiority over existing approaches.
Theory of Events Roberts, Chris; Dolasinski, Mary Jo; Reynolds, Joel ...
Journal of hospitality & tourism research (Washington, D.C.),
08/2022, Volume:
46, Issue:
6
Journal Article
Peer reviewed
Event management research has generally had a focus on the operational aspect of providing events. In this conceptual effort, the elements of an event are examined through the perspective of the ...attendee. Five key components of the event experience are identified and explored. Together, the five elements are used to build a model that presents the multifaceted nature of the attendee’s experience. The model is used as a basis for the theory of events to explain and predict what a participant needs and expects from an event experience.
We present adversarial event prediction (AEP), a novel approach to detecting abnormal events through an event prediction setting. Given normal event samples, AEP derives the prediction model, which ...can discover the correlation between the present and future of events in the training step. In obtaining the prediction model, we propose adversarial learning for the past and future of events. The proposed adversarial learning enforces AEP to learn the representation for predicting future events and restricts the representation learning for the past of events. By exploiting the proposed adversarial learning, AEP can produce the discriminative model to detect an anomaly of events without complementary information, such as optical flow and explicit abnormal event samples in the training step. We demonstrate the efficiency of AEP for detecting anomalies of events using the UCSD-Ped, CUHK Avenue, Subway, and UCF-Crime data sets. Experiments include the performance analysis depending on hyperparameter settings and the comparison with existing state-of-the-art methods. The experimental results show that the proposed adversarial learning can assist in deriving a better model for normal events on AEP, and AEP trained by the proposed adversarial learning can surpass the existing state-of-the-art methods.
Event-by-event fluctuations in the elliptic-flow coefficient v2 are studied in PbPb collisions at sNN=5.02 TeV using the CMS detector at the CERN LHC. Elliptic-flow probability distributions p(v2) ...for charged particles with transverse momentum 0.3<pT<3.0GeV/c and pseudorapidity |η|<1.0 are determined for different collision centrality classes. The moments of the p(v2) distributions are used to calculate the v2 coefficients based on cumulant orders 2, 4, 6, and 8. A rank ordering of the higher-order cumulant results and nonzero standardized skewness values obtained for the p(v2) distributions indicate non-Gaussian initial-state fluctuations. Bessel–Gaussian and elliptic power fits to the flow distributions are studied to characterize the initial-state spatial anisotropy.
Event-triggered consensus of multiagent systems (MASs) has attracted tremendous attention from both theoretical and practical perspectives due to the fact that it enables all agents eventually to ...reach an agreement upon a common quantity of interest while significantly alleviating utilization of communication and computation resources. This paper aims to provide an overview of recent advances in event-triggered consensus of MASs. First, a basic framework of multiagent event-triggered operational mechanisms is established. Second, representative results and methodologies reported in the literature are reviewed and some in-depth analysis is made on several event-triggered schemes, including event-based sampling schemes, model-based event-triggered schemes, sampled-data-based event-triggered schemes, and self-triggered sampling schemes. Third, two examples are outlined to show applicability of event-triggered consensus in power sharing of microgrids and formation control of multirobot systems, respectively. Finally, some challenging issues on event-triggered consensus are proposed for future research.
This paper is intended to solve the fully distributed and observer-based consensus control problem of multi-agent systems with general linear dynamics under event-triggered communication (ETC). Two ...novel event-triggered strategies named adaptive dynamic event-triggered (ADET) schemes for one-to-all and one-to-one ETC are well developed, in which on-line triggering parameters associated with each node or edge and dynamic thresholds with updating laws are introduced, respectively. Firstly, an ADET consensus control protocol under one-to-all ETC is proposed and a sufficient condition for consensus is derived. Compared with most existing triggering rules, the on-line triggering parameter associated with each node makes the controller be designed in a fully distributed way. On the other hand, the proposed dynamic threshold has the potential of excluding Zeno behavior without sacrificing the system performance. Secondly, an ADET consensus control protocol under one-to-one ETC is studied, in which each agent asynchronously transmits its observer states to its neighbors depending on edge-based triggering functions. The one-to-one ETC provides a flexible self-regulated transmission mode. An effective fully distributed and observer-based consensus protocol is developed appropriately with available local measurement outputs, under which the agents are not required to have a priori knowledge of any global information. Further discussion on the efficiency of ADET strategies and comparison between state-based and observer-based ADET control are provided to enrich the distributed resources-aware control framework. Finally, one simulation example is provided to illustrate the theoretical results.
Organic-rich rocks (averaging 2–5% total organic carbon) and positive carbonate-carbon isotope excursions (δC13>+5‰ and locally much higher, i.e. the Lomagundi-Jatuli Event) are hallmark features of ...Palaeoproterozoic successions and are assumed to archive a global event of unique environmental conditions following the c. 2.3 Ga Great Oxidation Event. Here we combine new and published geochronology that shows that the main Palaeoproterozoic carbon burial episodes (CBEs) preserved in Russia, Gabon and Australia were temporally discrete depositional events between c. 2.10 and 1.85 Ga. In northwest Russia we can also show that timing of the termination of the Lomagundi-Jatuli Event may have differed by up to 50 Ma between localities, and that Ni mineralisation occurred at c. 1920 Ma. Further, CBEs have traits in common with Mesozoic Oceanic Anoxic Events (OAEs); both are exceptionally organic-rich relative to encasing strata, associated with contemporaneous igneous activity and marked by organic carbon isotope profiles that exhibit a stepped decrease followed by a stabilisation period and recovery. Although CBE strata are thicker and of greater duration than OAEs (100 s of metres versus metres, ∼106 years versus ∼105 years), their shared characteristics hint at a commonality of cause(s) and feedbacks. This suggests that CBEs represent processes that can be either basin-specific or global in nature and a combination of circumstances that are not unique to the Palaeoproterozoic. Our findings urge circumspection and re-consideration of models that assume CBEs are a Deep Time singularity.
•Palaeoproterozoic carbon burial episodes (CBE) and excursions are temporally discrete.•Zircon ID-TIMS yields Russian CBE ages at c. 1.97 (Onega) and c. 1.92 Ga (Pechenga).•Temporal relationship between Large Igneous Provinces and CBE.•Similarities noted between Palaeoproterozoic CBE and Mesozoic Ocean Anoxic Events.•We suggest biogeochemical processes analogous to modern ones post the GOE.
•This paper illustrates an application of the ISA methodology to quantify the risk reduction by means of FLEX and usual recovery strategies.•The impact of portable equipment and AFW recovery ...strategies on Damage Exceedance Frequency of TLFW sequences has been evaluated, as well as the RCP trip and F&B start time.•The FLEX strategies lead to a significant risk reduction in TLFW sequences.•The installation time of portable equipment is a key factor for FLEX strategies success.
After the accident at Fukushima Dai-ichi, considerable efforts were put on enhancing the capability of the Nuclear Power Plants to cope with conditions resulting from the loss of plant safety-related systems. The most widespread solution adopted worldwide has been to define and implement new procedures and emergency actuation plans, the so called FLEX strategies. Among these strategies, there are several recovery strategies which involve the use of portable equipment for accomplishing the safety functions of the unavailable systems. In some cases, these strategies have been devised to be performed concurrently to the usual system recovery procedures included in the EOPs of most NPPs. In this regard, the heat sink recovery after the occurrence of a Total Loss of Feedwater (TLFW) in a Westinghouse 3-loop PWR design is a significant example, and it has been chosen in the present study to assess the quantitative risk reduction provided by the usual and FLEX recovery strategies in a Westinghouse 3-loop PWR design. With this aim, the Integrated Safety Assessment (ISA) methodology, developed by the Spanish Nuclear Safety Council (CSN), has been applied to TLFW sequences as part of the collaboration between Technical University of Madrid (UPM), NFQ Solutions and CSN.
Supervisory control of fuzzy discrete event systems under partial observation is investigated in the paper. Without loss of generality, we consider fuzzy discrete event systems with constraints where ...a fuzzy discrete event system is modeled by a fuzzy automaton. Sequences of events that can be generated by the system are regarded as constraints and are modeled by a crisp automaton. A supervisor is designed to control the fuzzy discrete event system so that the supervised system is prevented from entering a pre-specified set of illegal/unsafe fuzzy states. A necessary and sufficient condition for the existence of a supervisor is obtained. When the condition is satisfied, an online supervisor can be designed. Fuzzy state estimation problem is first solved, as the supervisor is fuzzy-state-estimate-based. A method is developed to estimate fuzzy state iteratively after observation of each new event. We show that the supervisor so developed ensures the safety of the system and is least restrictive among all possible safe supervisors. Potential of the theoretical results for real-world applications is illustrated through an example of HIV/AIDS treatment decision-making.
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