Clustering uncertain trajectories

Knowledge discovery in Trajectory Databases (TD) is an emerging field which has recently gained great interest. On the other hand, the inherent presence of uncertainty in TD (e.g., due to GPS errors) has not been taken yet into account during the mining process. In this paper, we study the effect of uncertainty in TD clustering and introduce a three-step approach to deal with it. First, we propose an intuitionistic point vector representation of trajectories that encompasses the underlying uncertainty and introduce an effective distance metric to cope with uncertainty. Second, we devise CenTra, a novel algorithm which tackles the problem of discovering the Centroid Trajectory of a group of movements taking into advantage the local similarity between portions of trajectories. Third, we propose a variant of the Fuzzy C-Means (FCM) clustering algorithm, which embodies CenTra at its update procedure. Finally, we relax the vector representation of the Centroid Trajectories by introducing an algorithm that post-processes them, as such providing these mobility patterns to the analyst with a more intuitive representation. The experimental evaluation over synthetic and real world TD demonstrates the efficiency and effectiveness of our approach.     

Overlapping B-trees: An implementation of a transaction time access method

A new variation of Overlapping B⁺-trees is presented, which provides efficient indexing of transaction time and keys in a two dimensional key-time space. Modification operations (i.e. insertions, deletions and updates) are allowed at the current version, whereas queries are allowed to any temporal version, i.e. either in the current or in past versions. Using this structure, snapshot and range-timeslice queries can be answered optimally. However, the fundamental objective of the proposed method is to deliver efficient performance in case of a general pure-key query (i.e. ‘history of a key’). The trade-off is a small increase in time cost for version operations and storage requirements.     

Growing triples on trees: an XML-RDF hybrid model for annotated documents

Since the beginning of the Semantic Web initiative, significant efforts have been invested in finding efficient ways to publish, store, and query metadata on the Web. RDF and SPARQL have become the standard data model and query language, respectively, to describe resources on the Web. Large amounts of RDF data are now available either as stand-alone datasets or as metadata over semi-structured (typically XML) documents. The ability to apply RDF annotations over XML data emphasizes the need to represent and query data and metadata simultaneously. We propose XR, a novel hybrid data model capturing the structural aspects of XML data and the semantics of RDF, also enabling us to reason about XML data. Our model is general enough to describe pure XML or RDF datasets, as well as RDF-annotated XML data, where any XML node can act as a resource. This data model comes with the XRQ query language that combines features of both XQuery and SPARQL. To demonstrate the feasibility of this hybrid XML-RDF data management setting, and to validate its interest, we have developed an XR platform on top of well-known data management systems for XML and RDF. In particular, the platform features several XRQ query processing algorithms, whose performance is experimentally compared.     

Road safety performance indicators for the interurban road network

Various road safety performance indicators (SPIs) have been proposed for different road safety research areas, mainly as regards driver behaviour (e.g. seat belt use, alcohol, drugs, etc.) and vehicles (e.g. passive safety); however, no SPIs for the road network and design have been developed. The objective of this research is the development of an SPI for the road network, to be used as a benchmark for cross-region comparisons. The developed SPI essentially makes a comparison of the existing road network to the theoretically required one, defined as one which meets some minimum requirements with respect to road safety. This paper presents a theoretical concept for the determination of this SPI as well as a translation of this theory into a practical method. Also, the method is applied in a number of pilot countries namely the Netherlands, Portugal, Greece and Israel. The results show that the SPI could be efficiently calculated in all countries, despite some differences in the data sources. In general, the calculated overall SPI scores were realistic and ranged from 81 to 94%, with the exception of Greece where the SPI was relatively lower (67%). However, the SPI should be considered as a first attempt to determine the safety level of the road network. The proposed method has some limitations and could be further improved. The paper presents directions for further research to further develop the SPI.     

A Low-Voltage 5-GHz Downconversion Mixer Employing A Second Harmonic Injection Linearization Technique

In this paper, a low-voltage CMOS mixer topology, appropriate for operation in the 5-GHz frequency band, is presented. The mixer combines several design techniques in order to achieve high linearity performance with minimum current consumption in a restricted 1-V supply. The proposed mixer utilizes an integrated transformer to improve the high frequency performance and to achieve large LO to RF isolation. In addition, a novel linearization technique based on second harmonic injection, is introduced to optimize linearity performance. The design is being implemented in a 0.13-mum CMOS technology.     

A link adaptation scheme optimized for wireless JPEG 2000 transmission over realistic MIMO systems

This paper proposes a Joint Source Channel Coding solution optimized for a wireless JPEG 2000 (JPWL ISO/IEC 15444-11) image transmission scheme over a MIMO channel. To ensure robustness of the transmission, channel diversity is exploited with a Closed-Loop MIMO-OFDM scheme. This relies on the Channel State Information (CSI) knowledge on the transmitter side, which allows the MIMO channel to be decomposed into several hierarchical SISO subchannels. In the proposed scheme, the JPWL codestream is divided into hierarchical quality layer passing through the SISO subchannels. With the CSI, a global and optimal method for adjusting all the system parameters of each SISO subchannel is provided. Accordingly, adaptive modulation, Unequal Error Protection (UEP), Unequal Power Allocation (UPA) and source coding rate is provided for each quality layers. The major strength of this work is to provide an optimal method that parameterizes several variables. These have an effect on the rate-distortion trade-off under bitrate, Quality of Service (QoS) and power constraints. Finally, the proposed work allows flexible and reactive coding of a JPWL codestream adapted to the instantaneous channel status. The performance of this technique is evaluated over a realistic time-varying MIMO channel provided by a 3D-ray tracing propagation model. A significant improvement in the quality of the image is demonstrated.     

Adaptive component composition and load balancing for distributed stream processing applications

Providing real-time and QoS support to stream processing applications running on top of large-scale overlays is challenging due to the inherent heterogeneity and resource limitations of the nodes and the multiple QoS demands of the applications that must concurrently be met. In this paper we propose an integrated adaptive component composition and load balancing mechanism that (1) allows the composition of distributed stream processing applications on the fly across a large-scale system, while satisfying their QoS demands and distributing the load fairly on the resources, and (2) adapts dynamically to changes in the resource utilization or the QoS requirements of the applications. Our extensive experimental results using both simulations as well as a prototype deployment illustrate the efficiency, performance and scalability of our approach.

Civil Society in Times of Crisis: Understanding Collective Action Dynamics in Digitally‐Enabled Volunteer Networks

Social media play an important role in political mobilization. Voluntary engagement can especially benefit from new opportunities for organizing collective action. Although research has explored the use of Twitter by decentralized individuals for this, there has been little emphasis on its use for community engagement and the provision of public goods. Even less is known about its role in the emergence and offline expansion of spontaneous self‐organized solidarity initiatives. This paper investigates how networked communication facilitates self‐organization and the development of ties in a network of volunteers in Greece. To examine whether initiative‐specific community feelings that can transcend online‐offlsine divides evolve in such hybrid networks, the analysis is complemented with individual‐level data drawn from a survey with the initiative's volunteers.