Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.

Log delta analysis: Interpretable differencing of Business process event logs

This paper addresses the problem of identifying and explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Analysis of Business Process Variants in Apromore

In this paper we illustrate a set of features of the Apromore process model repository for analyzing business process variants. Two types of analysis are provided: one is static and based on differences on the process control flow, the other is dynamic and based on differences in the process behavior between the variants. These features combine techniques for the management of large process model collections with those for mining process knowledge from process execution logs. The tool demonstration will be useful for researchers and practitioners working on large process model collections and process execution logs, and specifically for those with an interest in understanding, managing and consolidating business process variants both within and across organizational boundaries.

Sustaining productivity of a Vertosol at Warra, Queensland, with fertilisers, no-tillage or legumes. 8. Effect of duration of lucerne ley on soil nitrogen and water, wheat yield and protein.

Soil nitrogen (N) supply in the Vertosols of southern Queensland, Australia has steadily declined as a result of long-term cereal cropping without N fertiliser application or rotations with legumes. Nitrogen-fixing legumes such as lucerne may enhance soil N supply and therefore could be used in lucerne-wheat rotations. However, lucerne leys in this subtropical environment can create a soil moisture deficit, which may persist for a number of seasons. Therefore, we evaluated the effect of varying the duration of a lucerne ley (for up to 4 years) on soil N increase, N supply to wheat, soil water changes, wheat yields and wheat protein on a fertility-depleted Vertosol in a field experiment between 1989 and 1996 at Warra (26degrees 47'S, 150degrees53'E), southern Queensland. The experiment consisted of a wheat-wheat rotation, and 8 treatments of lucerne leys starting in 1989 (phase 1) or 1990 (phase 2) for 1,2,3 or 4 years duration, followed by wheat cropping. Lucerne DM yield and N yield increased with increasing duration of lucerne leys. Soil N increased over time following 2 years of lucerne but there was no further significant increase after 3 or 4 years of lucerne ley. Soil nitrate concentrations increased significantly with all lucerne leys and moved progressively downward in the soil profile from 1992 to 1995. Soil water, especially at 0.9-1.2 m depth, remained significantly lower for the next 3 years after the termination of the 4 year lucerne ley than under continuous wheat. No significant increase in wheat yields was observed from 1992 to 1995, irrespective of the lucerne ley. However, wheat grain protein concentrations were significantly higher under lucerne-wheat than under wheat wheat rotations for 3-5 years. The lucerne yield and soil water and nitrate-N concentrations were satisfactorily simulated with the APSIM model. Although significant N accretion occurred in the soil following lucerne leys, in drier seasons, recharge of the drier soil profile following long duration lucerne occurred after 3 years. Consequently, 3- and 4-year lucerne-wheat rotations resulted in more variable wheat yields than wheat-wheat rotations in this region. The remaining challenge in using lucerne-wheat rotations is balancing the N accretion benefits with plant-available water deficits, which are most likely to occur in the highly variable rainfall conditions of this region.

Clinical signs and duration of cyanide toxicosis delivered by the M-44 ejector in wild dogs

Sodium cyanide poison is potentially a more humane method to control wild dogs than sodium fluoroacetate (1080) poison. This study quantified the clinical signs and duration of cyanide toxicosis delivered by the M-44 ejector. The device delivered a nominal 0.88 g of sodium cyanide, which caused the animal to loose the menace reflex in a mean of 43 s, and the animal was assumed to have undergone cerebral hypoxia after the last visible breath. The mean time to cerebral hypoxia was 156 s for a vertical pull and 434 s for a side pull. The difference was possibly because some cyanide may be lost in a side pull. There were three distinct phases of cyanide toxicosis: the initial phase was characterised by head shaking, panting and salivation; the immobilisation phase by incontinence, ataxia and loss of the righting reflex; and the cerebral hypoxia phase by a tetanic seizure. Clinical signs that were exhibited in more than one phase of cyanide toxicosis included retching, agonal breathing, vocalisation, vomiting, altered levels of ocular reflex, leg paddling, tonic muscular spasms, respiratory distress and muscle fasciculations of the muzzle.

Estimating and influencing the duration of weed eradication programmes

1. Weed eradication efforts often must be sustained for long periods owing to the existence of persistent seed banks, among other factors. Decision makers need to consider both the amount of investment required and the period over which investment must be maintained when determining whether to commit to (or continue) an eradication programme. However, a basis for estimating eradication programme duration based on simple data has been lacking. Here, we present a stochastic dynamic model that can provide such estimates. 2. The model is based upon the rates of progression of infestations from the active to the monitoring state (i.e. no plants detected for at least 12 months), rates of reversion of infestations from monitoring to the active state and the frequency distribution of time since last detection for all infestations. Isoquants that illustrate the combinations of progression and reversion parameters corresponding to eradication within different time frames are generated. 3. The model is applied to ongoing eradication programmes targeting branched broomrape Orobanche ramosa and chromolaena Chromolaena odorata. The minimum periods in which eradication could potentially be achieved were 22 and 23 years, respectively. On the basis of programme performance until 2008, however, eradication is predicted to take considerably longer for both species (on average, 62 and 248 years, respectively). Performance of the branched broomrape programme could be best improved through reducing rates of reversion to the active state; for chromolaena, boosting rates of progression to the monitoring state is more important. 4. Synthesis and applications. Our model for estimating weed eradication programme duration, which captures critical transitions between a limited number of states, is readily applicable to any weed.Aparticular strength of the method lies in its minimal data requirements. These comprise estimates of maximum seed persistence and infested area, plus consistent annual records of the detection (or otherwise) of the weed in each infestation. This work provides a framework for identifying where improvements in management are needed and a basis for testing the effectiveness of alternative tactics. If adopted, our approach should help improve decision making with regard to eradication as a management strategy.

The state of the art of business process management research as published in the BPM Conference

The research field of Business Process Management (BPM) has gradually developed as a discipline situated within the computer, management and information systems sciences. Its evolution has been shaped by its own conference series, the BPM conference. Still, as with any other academic discipline, debates accrue and persist, which target the identity as well as the quality and maturity of the BPM field. In this paper, we contribute to the debate on the identity and progress of the BPM conference research community through an analysis of the BPM conference proceedings. We develop an understanding of signs of progress of research presented at this conference, where, how, and why papers in this conference have had an impact, and the most appropriate formats for disseminating influential research in this conference. Based on our findings from this analysis, we provide conclusions about the state of the conference series and develop a set of recommendations to further develop the conference community in terms of research maturity, methodological advance, quality, impact, and progression.

Recommendations from analyzing the state-of-the-art of business process management research

Business Process Management (BPM) as a research field integrates different perspectives from the disciplines computer science, management science and information systems research. Its evolution has by been shaped by the corresponding conferences series, the International Conference on Business Process Management (BPM conference). As much as in other academic discipline, there is an ongoing debate that discusses the identity, the quality and maturity of the BPM field. In this paper, we review and summarize the major findings a larger study that will be published in the Business & Information Systems Engineering journal in 2016. In the study, we investigate the identity and progress of the BPM conference research community through an analysis of the BPM conference proceedings. Based on our findings from this analysis, we formulate recommendations to further develop the conference community in terms of methodological advance, quality, impact and progression.

The perturbational treatment of the process of hydrogen abstraction by ketones

The change in energy during hydrogen abstraction by ketones is estimated for different electronic states as a function of the intermolecular orbital overlap employing perturbation theory. The results suggest that ketones preferentially undergo the in-plane reaction and abstract a hydrogen atom in their triplet nπ* state. For ketones where the triplet ππ* state lies below the triplet nπ* state, hydrogen abstraction can take place in the ππ* state owing to the crossing of the zero order reaction surfaces of the nπ* and ππ* states.

Automated Discovery of Structured Process Models: Discover Structured vs. Discover and Structure

This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.

Duration of a lightning flash

The mean duration of a lightning flash is observed to exhibit systematic variation with the growth and decay of the activity of a thundercloud and reaches a minimum value when the radio noise level and rate of flashing are at their maximum values.

Fiber Bragg Grating Sensors for Real Time Monitoring of Evacuation Process

Fiber bragg grating (FBG) sensors have been widely used for number of sensing applications like temperature, pressure, acousto-ultrasonic, static and dynamic strain, refractive index change measurements and so on. Present work demonstrates the use of FBG sensors in in-situ measurement of vacuum process with simultaneous leak detection capability. Experiments were conducted in a bell jar vacuum chamber facilitated with conventional Pirani gauge for vacuum measurement. Three different experiments have been conducted to validate the performance of FBG sensor in monitoring vacuum creating process and air bleeding. The preliminary results of FBG sensors in vacuum monitoring have been compared with that of commercial Pirani gauge sensor. This novel technique offers a simple alternative to conventional method for real time monitoring of evacuation process. Proposed FBG based vacuum sensor has potential applications in vacuum systems involving hazardous environment such as chemical and gas plants, automobile industries, aeronautical establishments and leak monitoring in process industries, where the electrical or MEMS based sensors are prone to explosion and corrosion.