Cross-Layer Peer-to-Peer Track Identification and Optimization Based on Active Networking

P2P applications appear to emerge as ultimate killer applications due to their ability to construct highly dynamic overlay topologies with rapidly-varying and unpredictable traffic dynamics, which can constitute a serious challenge even for significantly over-provisioned IP networks. As a result, ISPs are facing new, severe network management problems that are not guaranteed to be addressed by statically deployed network engineering mechanisms. As a first step to a more complete solution to these problems, this paper proposes a P2P measurement, identification and optimisation architecture, designed to cope with the dynamicity and unpredictability of existing, well-known and future, unknown P2P systems. The purpose of this architecture is to provide to the ISPs an effective and scalable approach to control and optimise the traffic produced by P2P applications in their networks. This can be achieved through a combination of different application and network-level programmable techniques, leading to a crosslayer identification and optimisation process. These techniques can be applied using Active Networking platforms, which are able to quickly and easily deploy architectural components on demand. This flexibility of the optimisation architecture is essential to address the rapid development of new P2P protocols and the variation of known protocols

Activity-Aware Electrocardiogram-based Passive Ongoing Biometric Verification

Identity fraud due to lost, stolen or shared information or tokens that represent an individual\u27s identity is becoming a growing security concern. Biometric recognition - the identification or verification of claimed identity, shows great potential in bridging some of the existing security gaps. It has been shown that the human Electrocardiogram (ECG) exhibits sufficiently unique patterns for use in biometric recognition. But it also exhibits significant variability due to stress or activity, and signal artifacts due to movement. In this thesis, we develop a novel activity-aware ECG-based biometric recognition scheme that can verify/identify under different activity conditions. From a pattern recognition standpoint, we develop algorithms for preprocessing, feature extraction and probabilistic classification. We pay particular attention to the applicability of the proposed scheme in ongoing biometric verification of claimed identity. Finally we propose a wearable prototype architecture of our scheme

Applications of Trajectory Data From the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study

Transportation agencies have an opportunity to leverage increasingly-available trajectory datasets to improve their analyses and decision-making processes. However, this data is typically purchased from vendors, which means agencies must understand its potential benefits beforehand in order to properly assess its value relative to the cost of acquisition. While the literature concerned with trajectory data is rich, it is naturally fragmented and focused on technical contributions in niche areas, which makes it difficult for government agencies to assess its value across different transportation domains. To overcome this issue, the current paper explores trajectory data from the perspective of a road transportation agency interested in acquiring trajectories to enhance its analyses. The paper provides a literature review illustrating applications of trajectory data in six areas of road transportation systems analysis: demand estimation, modeling human behavior, designing public transit, traffic performance measurement and prediction, environment and safety. In addition, it visually explores 20 million GPS traces in Maryland, illustrating existing and suggesting new applications of trajectory data

Visualizing Business Process Deviance With Timeline Diagrams

Lõputöös püstitatakse kaks peamist küsimust mõiste "hälvete kaevandamine" kohta ja tehakse ettepanek uue meetodi jaoks, mis näitab kahe sündmuse logide erinevusi ajalise dünaamika mõttes, et täita hälvete kaevandamist. Hälvete kaevandamise eesmärk on täpsustada probleemide päritolu ja kõrvalekaldeid. Kogu sellega seotud töö uurimisel on täheldatud, et enamus olemasolevatest meetoditest keskenduvad protsessi põhistruktuurile, mis on ülesannete täitmise järjekord. Uus tehnika näitab tavapäraste ja hälbivate jälgede tegevuste suhtelisi kestusi, st ajalist dünaamikat, joonistades variantide ajakava. Lisaks pakutakse välja tehnika, mis näitab diagrammide kohandamiseks erinevaid seadeid, nagu tulemuslikkuse mõõdik ja protsessi üksikasjalikkus. Lõpuks onvälja arendatud kontseptsioonivahend, mis järgib välja pakutud lähenemisviisi ja on veebis saadaval.The thesis poses two main questions regarding to the notion of “deviance mining” andproposes a new technique to visualise the differences of two event logs in terms oftemporal dynamics in order to perform deviance mining. The objective of deviancemining is to pinpoint the origin of the problems and the deviance. Throughout theresearch of the related work it’s observed that most of the existing methods focus on themain structure of the process which is the order of the tasks being executed. The newtechnique brings out the relative durations i.e temporal dynamics of the activities in thenormal and deviant traces by drawing a timeline diagram of the variants. Additionally theproposed technique puts forward set of different settings such as the performancemeasure and the granularity level of the process to customize the diagram. Lastly, aproof-of-concept tool abiding by the proposed approach is implemented which is servedon the web

(Non-)Sharing as a Form of Maternal Care? The Ambiguous Meanings of Sharenting for Mothers of 0- To-8-Year-Old Children

The present article reports on findings from a survey administered in (country anonymised) to a national representative sample of parents of children aged 0-8 around their sharenting behaviour. We first frame sharenting as a complex phenomenon where gendered, generational and agentic matters intertwine and mingle in complex ways. We then report results from a cluster analysis aimed at identifying different sharenting styles reflecting the scale and scope of parents’ sharing behaviour among our sample. The relationships between sharenting styles and parents’ socio-demographics, as well as parental practices of privacy management are further explored and reported. Altogether, findings provide insights into the experience of sharenting in family life pointing to a variety of sharing practices, while also showing first that sharenting represents a key site of identity performance for young mothers, and then how parents negotiate and manage related issues of agency and privacy

An event-related potential study on changes of violation and error responses during morphosyntactic learning

Based on recent findings showing electrophysiological changes in adult language learners after relatively short periods of training, we hypothesized that adult Dutch learners of German would show responses to German gender and adjective declension violations after brief instruction. Adjective declension in German differs from previously studied morphosyntactic regularities in that the required suffixes depend not only on the syntactic case, gender, and number features to be expressed, but also on whether or not these features are already expressed on linearly preceding elements in the noun phrase. Violation phrases and matched controls were presented over three test phases (pretest and training on the first day, and a posttest one week later). During the pretest, no electrophysiological differences were observed between violation and control conditions, and participants’ classification performance was near chance. During the training and posttest phases, classification improved, and there was a P600-like violation response to declension but not gender violations. An error-related response during training was associated with improvement in grammatical discrimination from pretest to posttest. The results show that rapid changes in neuronal responses can be observed in adult learners of a complex morphosyntactic rule, and also that error-related electrophysiological responses may relate to grammar acquisition

Conformance checking: A state-of-the-art literature review

Conformance checking is a set of process mining functions that compare process instances with a given process model. It identifies deviations between the process instances' actual behaviour ("as-is") and its modelled behaviour ("to-be"). Especially in the context of analyzing compliance in organizations, it is currently gaining momentum -- e.g. for auditors. Researchers have proposed a variety of conformance checking techniques that are geared towards certain process model notations or specific applications such as process model evaluation. This article reviews a set of conformance checking techniques described in 37 scholarly publications. It classifies the techniques along the dimensions "modelling language", "algorithm type", "quality metric", and "perspective" using a concept matrix so that the techniques can be better accessed by practitioners and researchers. The matrix highlights the dimensions where extant research concentrates and where blind spots exist. For instance, process miners use declarative process modelling languages often, but applications in conformance checking are rare. Likewise, process mining can investigate process roles or process metrics such as duration, but conformance checking techniques narrow on analyzing control-flow. Future research may construct techniques that support these neglected approaches to conformance checking

Knowing Your Population: Privacy-Sensitive Mining of Massive Data

Location and mobility patterns of individuals are important to environmental planning, societal resilience, public health, and a host of commercial applications. Mining telecommunication traffic and transactions data for such purposes is controversial, in particular raising issues of privacy. However, our hypothesis is that privacy-sensitive uses are possible and often beneficial enough to warrant considerable research and development efforts. Our work contends that peoples behavior can yield patterns of both significant commercial, and research, value. For such purposes, methods and algorithms for mining telecommunication data to extract commonly used routes and locations, articulated through time-geographical constructs, are described in a case study within the area of transportation planning and analysis. From the outset, these were designed to balance the privacy of subscribers and the added value of mobility patterns derived from their mobile communication traffic and transactions data. Our work directly contrasts the current, commonly held notion that value can only be added to services by directly monitoring the behavior of individuals, such as in current attempts at location-based services. We position our work within relevant legal frameworks for privacy and data protection, and show that our methods comply with such requirements and also follow best-practice