Event-oriented Model Research Articles

Event-oriented model of data flow control between embedded devices of a ground-based robotic vehicle

This paper discusses methods for extracting significant events from data streams generated by actuating and sen-sory devices built into robotic means. An event-oriented model for managing data streams between embedded devices of a ground-based robotic vehicle using a knowledge base that stores information about embedded de-vices and their configurations has been developed. To isolate significant events from the streams of data generat-ed by devices, the restrictions described in the device configurations are used. The proposed model also takes into account possible device failures. The generated events initiate the selection and launch of a certain process by a robotic means, for the description of which BPMN notation is used. The results of simulation modeling are shown, which confirm the effectiveness of the proposed event-oriented model, which provides a 41.8% reduction in data volumes processed by the central computer due to the distribution of calculations to the intermediate microcontrol-lers of embedded devices.

Driver Psychology Latent Classes as Predictors of Traffic Incident Occurrence in Naturalistic Driving Study Data

Crash risk depends on several factors, driver factors being the most significant of all. Previous studies have tended to use roadway and driver demographic information to explain crash risk, overlooking driver psychological characteristics, which are also important for crash risk estimation. Crash data from police reports are available only for reportable crashes and do not detail driver characteristics or comparable information on driving activities. Naturalistic driving studies (NDSs) offer unique opportunities to obtain information about driver attributes, behavior, or other precrash factors for predicting crash occurrence. This study estimated NDS event-oriented models to evaluate the interaction between driver attributes and roadway environmental factors for predicting safety critical events. A latent class clustering approach was used to uncover categories of drivers by psychological, perceptual, and cognitive characteristics, and by driving experience. The results revealed four driver types: risk-taker, careful-impaired, careful-unimpaired, and distractible. These types were incorporated in mixed-effects binary logistic models, with roadway, traffic, and environmental variables to estimate and predict crash risk. The models that included driver factors more successfully predicted crash risk than those without. Risk-takers showed the highest probability of being in crashes. However, careful-impaired drivers—those whose impairments made it difficult to identify the location of another vehicle, visualize missing information, who had difficulties with visual–spatial perception and executive functioning—posed a higher crash risk in roadway conditions such as snow, lack of lane markings, and certain traffic operating conditions. The results point to novel avenues for educational and behavioral interventions to improve road safety.

Comparative Analysis of Degradation Assessment of Battery Energy Storage Systems in PV Smoothing Application

Photovoltaic (PV) generation depends on the availability of solar resources, being directly influenced by the variation in irradiance due to the presence of clouds over the PV panels, causing a variation in the power output. The use of battery energy storage systems integrated with the PV showed to be a technically feasible solution to mitigate these power output fluctuations within the maximum ramp limit. Most articles reported in the literature on smoothing PV power output, by coupling with battery degradation as performance indicators of the control strategy, used the event-oriented model that considers only the number of cycles and depth of discharge. This paper presents on the comparative analysis of two approaches to battery degradation models, an event-oriented model based on the Rainflow counting and a semiempirical model, and applies to photovoltaic power smoothing by using a wide range of restrictions and installed PV plant capacities. The semi-empirical degradation model revealed higher battery degradation for all simulated cases. For Strategy 2, the order was 50% higher than the event-oriented model, probably due to severe DR and RR, which increases the stress on the battery. For Strategy 1, the difference was greater, between 100% and 300%. The event-based model indicated that Strategy 1 implied less battery degradation, but the semi-empirical model indicated the opposite. Considering that the semi-empirical model considers more parameters of degradation, the fact that Strategy 2 implies less degradation is more reliable. Moreover, the result obtained by the SimSES model corroborates that the accelerated lithium cell battery degradation takes place, as the operation is at high SoC. Maintaining Ebat, reference is SoC 80% decreased the degradation in at least 25% with respect to degradation, maintaining Ebat, reference is SoC 100%. For this, Ebat, reference of the SoC control, can be designed to avoid operating under a high load state. The results demonstrated that choosing a simplified degradation model approach can lead to an error in the conclusion of which strategies are the best since calendar life effects are very important in the application of PV power smoothing.

EVENT ORIENTED MODELING RESTORING OPERABILITY OF LARGE-SCALE SOCIO-TECHNICAL SYSTEMS

This paper introduces an event-oriented four-component model for analyzing the efficiency of the fault diagnosis process. The simulation of the process of diagnostics and recovery of complex socio-technical systems allows for modeling either blind, either directed troubleshooting strategies.
 Also paper introduces criteria for the appropriateness of the intro-duction of diagnostic and troubleshooting systems with relating to diagnosing systems and the context of their use.

Distortions of the magnetic field by storm-time current systems in Earth's magnetosphere

Abstract. Magnetic field and current system changes in Earth's inner magnetosphere during storm times are studied using two principally different modeling approaches: on one hand, the event-oriented empirical magnetic field model, and, on the other, the Space Weather Modeling Framework (SWMF) built around a global MHD simulation. Two storm events, one moderate storm on 6–7 November 1997 with Dst minimum about −120 nT and one intense storm on 21–23 October 1999 with Dst minimum about −250 nT were modeled. Both modeling approaches predicted a large ring current (first partial, later symmetric) contribution to the magnetic field perturbation for the intense storm. For the moderate storm, the tail current plays a dominant role in the event-oriented model results, while the SWMF results showed no strong tail current in the main phase, which resulted in a poorly timed storm peak relative to the observations. These results imply that the the development of a ring current depends on a strong force to inject the particles deep into the inner magnetosphere, and that the tail current is an important external source for the distortions of the inner magnetospheric magnetic field for both storms. Neither modeling approach was able to reproduce all the variations in the Bx and By components observed at geostationary orbit by GOES satellites during these two storms: the magnetopause current intensifications are inadequate, and the field-aligned currents are not sufficiently represented. While the event-oriented model reproduces rather well the Bz component at geostationary orbit, including the substorm-associated changes, the SWMF field is too dipolar at these locations. The empirical model is a useful tool for validation of the first-principle based models such as the SWMF.

TEI and cultural heritage ontologies: Exchange of information?

The content in information systems and virtual reconstructions in the cultural heritage sector is to a large degree directly based on information deduced from the study of texts. In many cases, even if the texts are available electronically, the links from the deduced facts to the original texts are not available and in many cases very costly to re-establish. Reproducibility of results is a core concept in text-based research as in all research. Thus, such links should be expressed explicitly in the systems and in accordance with the data standards developed in the fields of text encoding and conceptual modelling. To do this it is necessary to create a combined understanding of text encoding represented by the TEI guidelines and the understanding of conceptual models represented by initiatives like the CIDOC CRM and FRBR oo . In this article, we study a part of this complex by comparing the expressive power of the real world descriptions TEI P5 by mapping central parts of the CIDOC CRM onto TEI P5. It is clear that the TEI P5 has moved a great step in the direction towards an event-oriented model compared with TEI P4. Our use of CIDOC CRM as a yardstick shows that the expressive-ness of TEI P5 can be greatly improved by extending the scope of very restricted elements like the relation element and adding a few new elements to the TEI.

Event-oriented Web-based E-trading

We address the problem of defining policies that may be used in the evaluation of requests made by client actors, in the course of web-based e-trading, to perform actions on the resources maintained by the server agents of an e-cooperative. An e-cooperative is a group of agents in cyberspace that may act individually or in conjunction with other agents to satisfy a client's request to act. Our principal contribution to this key problem is to define formally an event-oriented model in terms of which policies may be specified for helping to ensure that only legitimate forms of client actions are performed in the course of engaging in e-trading via the web. We call this model the Event-oriented Web-based E-trading (EWE) model . Policies defined in terms of the EWE model are used to specify a set of actions that client actors can perform as a consequence of the client having a particular status. We define the EWE model using a logic programming language and we give examples of web-based e-trading policy representation, validation and evaluation.

A DISTRIBUTION MODEL FOR EGG DEVELOPMENT IN MOUNTAIN PINE BEETLE

AbstractMountain pine beetle (Dendroctonus ponderosae Hopkins) population dynamics, as well as potential for outbreaks and resulting tree mortality, are related in part to habitat temperature. As a first step in development of a life-stage, event-oriented simulation model, we have modeled the temperature-dependent development of the egg stage. The completed model includes a full description of variation in developmental rates and is capable of predicting duration and eclosion patterns for any temperature regime. This model was parameterized using data obtained from constant-temperature experiments at temperatures of 8, 10, 12.5, 15, 20, 25, and 30°C. Validation experiments were conducted for constant temperatures of 15, 17.5, 22.5, and 27.5°C and for variable-temperature regimes of 15±5 and 15±10°C. Validation results indicated that the model is capable of accurately describing the emergence curve for constant temperatures below 27.5°C. The model also faithfully represents emergence under variable temperatures of 15 ± 10°C. Potential reasons for lack of model fidelity in describing emergence at constant high temperatures and for 15 ± 5°C are discussed in the text.

Computer Modeling of Rural Emergency Medical Services Delivery Systems

RURALSIM is a sophisticated computer simulation model designed as an aid in planning and evaluating rural emergency medical services (EMS) systems. Written in SIMULA, it has been successfully used in Indiana County, Pennsylvania, to study the potential effects of changes in existing vehicle placement and relocation strategies, vehicle dispatching policies and alternative forms of prehospital care, including the ability of the system to respond to a disaster.RURALSIM is a stochastic, dynamic, event-oriented computer model. Stochastic means that all random events, such as the occurrence of an incident, are generated according to appropriate probability distributions obtained from empirical data. Dynamic means that events occur over time and that the model selects the appropriate incident rates and response strategies for the particular time and day simulated.

Interactive verification of communication software on the basis of CIL

The CIL-approach for the development of communication services is based on the programming language CIL (Communication Service Implementation Language) and a CIL-compatible theory of program execution. The theory contains a first-order predicate calculus and an event-oriented model of program execution. The verification of programs written in CIL is supported by the automated generation of program axioms and by an interactive theorem prover tailored to the predicate calculus. Interactive verification during the design phase leads to early detection and localization of design errors and helps to reduce the efforts for debugging and testing. The paper describes the principles of the language, the theory, and the interactive verification tool. The design of a program realizing a transport service exemplifies the CIL-approach.