Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

Detecting drift from event streams of unpredictable business processes

Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art.

Liquid Business Process Model Collections

Many organizations realize that increasing amounts of data (“Big Data”) need to be dealt with intelligently in order to compete with other organizations in terms of efficiency, speed and services. The goal is not to collect as much data as possible, but to turn event data into valuable insights that can be used to improve business processes. However, data-oriented analysis approaches fail to relate event data to process models. At the same time, large organizations are generating piles of process models that are disconnected from the real processes and information systems. In this chapter we propose to manage large collections of process models and event data in an integrated manner. Observed and modeled behavior need to be continuously compared and aligned. This results in a “liquid” business process model collection, i.e. a collection of process models that is in sync with the actual organizational behavior. The collection should self-adapt to evolving organizational behavior and incorporate relevant execution data (e.g. process performance and resource utilization) extracted from the logs, thereby allowing insightful reports to be produced from factual organizational data.

Sustainability and Mission Drift in Microfinance

Microfinance institutions (MFIs) are constrained by double bottom-lines: meeting social obligations (the first bottom-line) and obtaining financial self-sufficiency (the second bottom-line). The proponents of the first bottom-line, however, are increasingly concerned that there is a trade-off between these two bottom-lines—i.e., getting hold of financial self-sufficiency may lead MFIs to drift away from their original social mission of serving the very poor, commonly known as mission drift in microfinance which is still a controversial issue. This study aims at addressing the concerns for mission drift in microfinance in a performance analysis framework. Chapter 1 deals with theoretical background, motivation and objectives of the topic. Then the study explores the validity of three major and related present-day concerns. Chapter 2 explores the impact of profitability on outreach-quality in MFIs, commonly known as mission drift, using a unique panel database that contains 4-9 years’ observations from 253 MFIs in 69 countries. Chapter 3 introduces factor analysis, a multivariate tool, in the process of analysing mission drift in microfinance and the exercise in this chapter demonstrates how the statistical tool of factor analysis can be utilised to examine this conjecture. In order to explore why some microfinance institutions (MFIs) perform better than others, Chapter 4 looks at factors which have an impact on several performance indicators of MFIs—profitability or sustainability, repayment status and cost indicators—based on quality-data on 353 institutions in 77 countries. The study also demonstrates whether such mission drift can be avoided while having self-sustainability. In Chapter 5 we examine the impact of capital and financing structure on the performance of microfinance institutions where estimations with instruments have been performed using a panel dataset of 782 MFIs in 92 countries for the period 2000-2007. Finally, Chapter 6 concludes the study by summarising the results from the previous chapters and suggesting some directions for future studies.

A Model of Evolutionay Drift

Drift appears to be crucial to study the stability properties of Nash equilibria in a component specifying different out-of-equilibrium behaviour. We propose a new microeconomic model of drift to be added to the learning process by which agents find their way to equilibrium. A key feature of the model is the sensitivity of the noisy agent to the proportion of agents in his player population playing the same strategy as his current one. We show that, 1. Perturbed Payoff-Positive and PayoffMonotone selection dynamics are capable of stabilizing pure non strict Nash equilibria in either singleton or nonsingleton component of equilibria; 2. The model is relevant to understand the role of drift in the behaviour observed in the laboratory for the Ultimatum Game and for predicting outcomes that can be experimentally tested. Hence, the selection dynamics model perturbed with the proposed drift may be seen as well as a new learning tool to understand observed behaviour.

Accurate measurement of carrier-envelope phase drift for infrared femtosecond laser pulses

A novel scheme to eliminate the artificial background phase jitter is proposed for measuring the carrier-envelope phase drift of tunable infrared femtosecond pulses from an OPA laser. Different from previous methods, a reference spectral interference measurement is performed, which reveals the artificial phase jitter in the measurement process, in addition to the normal f-to-2f interference measurement between the incident laser pulses and it second harmonic. By analyzing the interference fringes, the accurate CEP fluctuation of the incident pulses is obtained. (c) 2008 Optical Society of America

On the complexity of the water-gas shift reaction mechanism over a Pt/CeO2 catalyst: Effect of the temperature on the reactivity of formate surface species studied by operando DRIFT during isotopic transient at chemical steady-state

The present report investigates the role of formate species as potential reaction intermediates for the WGS reaction (CO + H2O -> CO2 + H-2) over a Pt-CeO2 catalyst. A combination of operando techniques, i.e., in situ diffuse reflectance FT-IR (DRIFT) spectroscopy and mass spectrometry (MS) during steady-state isotopic transient kinetic analysis (SSITKA), was used to relate the exchange of the reaction product CO2 to that of surface formate species. The data presented here suggest that a switchover from a non-formate to a formate-based mechanism could take place over a very narrow temperature range (as low as 60 K) over our Pt-CeO2 catalyst. This observation clearly stresses the need to avoid extrapolating conclusions to the case of results obtained under even slightly different experimental conditions. The occurrence of a low-temperature mechanism, possibly redox or Mars van Krevelen-like, that deactivates above 473 K because of ceria over-reduction is suggested as a possible explanation for the switchover, similarly to the case of the CO-NO reaction over Cu, I'd and Rh-CeZrOx (see Kaspar and co-workers [1-3]). (c) 2006 Elsevier B.V. All rights reserved.

Vägprojektering för minskade drift- och underhållskostnader : Brister och möjligheter

För att kunna bygga en ny väg måste den först planeras och projekteras. Vägplanering innebär att man undersöker förutsättningarna för att bygga vägen t.ex. konsekvenser för miljö, samhälle, trafiksäkerhet, framkomlighet, tillgänglighet samt tekniska och ekonomiska förutsättningar. Vägprojektering innebär att man bestämmer vägens utformning på detaljnivå t.ex. vägsträckning, bredd, profil, vägutrustning, etc. Planering och projektering av vägar är en komplicerad process med tanke på alla komponenter som en väg består av samt alla aspekter som man måste ta hänsyn till under vägens livstid. Planerings- och projekteringsprocessen utgör en avvägning av många aspekter för att hitta den optimala lösningen. Drift- och underhållsåtgärder på vägnätet föranleds ofta av att problem uppstått på ett fåtal ställen. Kostnaden för att åtgärda dessa ställen kan uppgå till stora belopp under vägens livslängd. Med en lämpligare utformning av vägen hade dessa problem i en del fall sannolikt kunnat undvikas. Bland de aktörer, som är inblandade i planerings- och projekteringsprocessen, finns det olika åsikter om orsaken till att man inte tar tillräcklig hänsyn till drift- och underhållaspekten under planerings- och projekteringsskedet. Vissa aktörer tycker att det är projektörens kunskapsbrister som leder till att vägen får olämplig utformning avseende drift och underhåll. Andra tycker att det är en kombination av olika brister hos väghållaren. Dessa brister kan då finnas i såväl planerings- och projekteringsprocessen som i drift- och underhållsprocessen. Denna rapport presenterar resultatet för en förstudie som har utförts inom doktorandprojektet ”Vägprojektering för minskade drift- och underhållskostnader”. Syftet med förstudien var att identifiera brister och problem på övergripande nivå som leder till att man inte tar tillräcklig hänsyn till drift- och underhållsaspekten vid planerings- och projekteringsprocessen. Ett annat syfte med förstudien var att föreslå förändringsbehov inom planerings- och projekteringsprocessen genom att analysera de identifierade problemen, analysera verksamheten vid planering och projektering, analysera verksamhetens mål, formulera nya mål för verksamheten och fastställa de nödvändiga förändringsbehoven.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

Spray adjuvant characteristics affecting agricultural spraying drift

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evolution of extrafloral nectaries: adaptive process and selective regime changes from forest to savanna

Much effort has been devoted to understanding the function of extrafloral nectaries (EFNs) for antplantherbivore interactions. However, the pattern of evolution of such structures throughout the history of plant lineages remains unexplored. In this study, we used empirical knowledge on plant defences mediated by ants as a theoretical framework to test specific hypotheses about the adaptive role of EFNs during plant evolution. Emphasis was given to different processes (neutral or adaptive) and factors (habitat change and trade-offs with new trichomes) that may have affected the evolution of antplant associations. We measured seven EFN quantitative traits in all 105 species included in a well-supported phylogeny of the tribe Bignonieae (Bignoniaceae) and collected field data on antEFN interactions in 32 species. We identified a positive association between ant visitation (a surrogate of ant guarding) and the abundance of EFNs in vegetative plant parts and rejected the hypothesis of phylogenetic conservatism of EFNs, with most traits presenting K-values < 1. Modelling the evolution of EFN traits using maximum likelihood approaches further suggested adaptive evolution, with static-optimum models showing a better fit than purely drift models. In addition, the abundance of EFNs was associated with habitat shifts (with a decrease in the abundance of EFNs from forest to savannas), and a potential trade-off was detected between the abundance of EFNs and estipitate glandular trichomes (i.e. trichomes with sticky secretion). These evolutionary associations suggest divergent selection between species as well as explains K-values < 1. Experimental studies with multiple lineages of forest and savanna taxa may improve our understanding of the role of nectaries in plants. Overall, our results suggest that the evolution of EFNs was likely associated with the adaptive process which probably played an important role in the diversification of this plant group.

In-situ DRIFT/MS study of the conversion of ethanol on mixed Mg/Si oxides

Due to the high price of natural oil and harmful effects of its usage, as the increase in emission of greenhouse gases, the industry focused in searching of sustainable types of the raw materials for production of chemicals. Ethanol, produced by fermentation of sugars, is one of the more interesting renewable materials for chemical manufacturing. There are numerous applications for the conversion of ethanol into commodity chemicals. In particular, the production of 1,3-butadiene whose primary source is ethanol using multifunctional catalysts is attractive. With the 25% of world rubber manufacturers utilizing 1,3-butadiene, there is an exigent need for its sustainable production. In this research, the conversion of ethanol in one-step process to 1,3-butadiene was studied. According to the literature, the mechanisms which were proposed to explain the way ethanol transforms into butadiene require to have both acid and basic sites. But still, there are a lot of debate on this topic. Thus, the aim of this research work is a better understanding of the reaction pathways with all the possible intermediates and products which lead to the formation of butadiene from ethanol. The particular interests represent the catalysts, based on different ratio Mg/Si in comparison to bare magnesia and silica oxides, in order to identify a good combination of acid/basic sites for the adsorption and conversion of ethanol. Usage of spectroscopictechniques are important to extract information that could be helpful for understanding the processes on the molecular level. The diffuse reflectance infrared spectroscopy coupled to mass spectrometry (DRIFT-MS) was used to study the surface composition of the catalysts during the adsorption of ethanol and its transformation during the temperature program. Whereas, mass spectrometry was used to monitor the desorbed products. The set of studied materials include MgO, Mg/Si=0.1, Mg/Si=2, Mg/Si=3, Mg/Si=9 and SiO2 which were also characterized by means of surface area measurements.

INTEGRATED MANAGEMENT OF THE INVASIVE SPECIES CIRSIUM ARVENSE, CANADA THISTLE, AND PHRAGMITES AUSTRALIS, COMMON REED: USING ECOLOGICALLY BASED CONTROL MEASURES AT EACH STAGE OF THE INVASION PROCESS

Invasive plant species threaten natural areas by reducing biodiversity and altering ecosystem functions. They also impact agriculture by reducing crop and livestock productivity. Millions of dollars are spent on invasive species control each year, and traditionally, herbicides are used to manage invasive species. Herbicides have human and environmental health risks associated with them; therefore, it is essential that land managers and stakeholders attempt to reduce these risks by utilizing the principles of integrated weed management. Integrated weed management is a practice that incorporates a variety of measures and focuses on the ecology of the invasive plant to manage it. Roadways are high risk areas that have high incidence of invasive species. Roadways act as conduits for invasive species spread and are ideal harborages for population growth; therefore, roadways should be a primary target for invasive species control. There are four stages in the invasion process which an invasive species must overcome: transport, establishment, spread, and impact. The aim of this dissertation was to focus on these four stages and examine the mechanisms underlying the progression from one stage to the next, while also developing integrated weed management strategies. The target species were Phragmites australis, common reed, and Cisrium arvense, Canada thistle. The transport and establishment risks of P. australis can be reduced by removing rhizome fragments from soil when roadside maintenance is performed. The establishment and spread of C. arvense can be reduced by planting particular resistant species, e.g. Heterotheca villosa, especially those that can reduce light transmittance to the soil. Finally, the spread and impact of C. arvense can be mitigated on roadsides through the use of the herbicide aminopyralid. The risks associated with herbicide drift produced by application equipment can be reduced by using the Wet-Blade herbicide application system.

The Emergence of Formal Control Specificity in Information Systems Outsourcing: A Process-View

Information systems (IS) outsourcing projects often fail to achieve initial goals. To avoid project failure, managers need to design formal controls that meet the specific contextual demands of the project. However, the dynamic and uncertain nature of IS outsourcing projects makes it difficult to design such specific formal controls at the outset of a project. It is hence crucial to translate high-level project goals into specific formal controls during the course of a project. This study seeks to understand the underlying patterns of such translation processes. Based on a comparative case study of four outsourced software development projects, we inductively develop a process model that consists of three unique patterns. The process model shows that the performance implications of emergent controls with higher specificity depend on differences in the translation process. Specific formal controls have positive implications for goal achievement if only the stakeholder context is adapted, while they are negative for goal achievement if in the translation process tasks are unintendedly adapted. In the latter case projects incrementally drift away from their initial direction. Our findings help to better understand control dynamics in IS outsourcing projects. We contribute to a process theoretic understanding of IS outsourcing governance and we derive implications for control theory and the IS project escalation literature.