Comparative Analysis of Five XML Query Languages

XML is becoming the most relevant new standard for data representation and exchange on the WWW. Novel languages for extracting and restructuring the XML content have been proposed, some in the tradition of database query languages (i.e. SQL, OQL), others more closely inspired by XML. No standard for XML query language has yet been decided, but the discussion is ongoing within the World Wide Web Consortium and within many academic institutions and Internet-related major companies. We present a comparison of five, representative query languages for XML, highlighting their common features and differences.Comment: TeX v3.1415, 17 pages, 6 figures, to be published in ACM Sigmod Record, March 200

Condition-based maintenance—an extensive literature review

This paper presents an extensive literature review on the field of condition-based maintenance (CBM). The paper encompasses over 4000 contributions, analysed through bibliometric indicators and meta-analysis techniques. The review adopts Factor Analysis as a dimensionality reduction, concerning the metric of the co-citations of the papers. Four main research areas have been identified, able to delineate the research field synthetically, from theoretical foundations of CBM; (i) towards more specific implementation strategies (ii) and then specifically focusing on operational aspects related to (iii) inspection and replacement and (iv) prognosis. The data-driven bibliometric results have been combined with an interpretative research to extract both core and detailed concepts related to CBM. This combined analysis allows a critical reflection on the field and the extraction of potential future research directions

The Locational Determinants of the U.S. Multinationals Activities

This paper examines empirically a range of theoretical hypotheses about the determinants of FDI location in a panel data regression framework. The results of the estimation of a gravity model lend support to the proximity-concentration and internalisation hypotheses. Also, the fact that FDI has been found to be decreasing in the competition posed by alternative locations is suggestive of the superiority of the share version of the gravity model over its classical formulation. A panel data cointegration-type analysis between FDI and GDP, and per capita income differential suggests that GDP has a positive impact on FDI, but provide mixed evidence as to whether per capita income differential reflects demand or supply determinants of FDI. Causality tests between income, income differential and FDI points to FDI playing a positive role on economic growth and convergence.

Contributions to QoS and energy efficiency in wi-fi networks

The Wi-Fi technology has been in the recent years fostering the proliferation of attractive mobile computing devices with broadband capabilities. Current Wi-Fi radios though severely impact the battery duration of these devices thus limiting their potential applications. In this thesis we present a set of contributions that address the challenge of increasing energy efficiency in Wi-Fi networks. In particular, we consider the problem of how to optimize the trade-off between performance and energy effciency in a wide variety of use cases and applications. In this context, we introduce novel energy effcient algorithms for real-time and data applications, for distributed and centralized Wi-Fi QoS and power saving protocols and for Wi-Fi stations and Access Points. In addition, the di¿erent algorithms presented in this thesis adhere to the following design guidelines: i) they are implemented entirely at layer two, and can hence be easily re-used in any device with a Wi-Fi interface, ii) they do not require modi¿cations to current 802.11 standards, and can hence be readily deployed in existing Wi-Fi devices, and iii) whenever possible they favor client side solutions, and hence mobile computing devices implementing them can benefit from an increased energy efficiency regardless of the Access Point they connect to. Each of our proposed algorithms is thoroughly evaluated by means of both theoretical analysis and packet level simulations. Thus, the contributions presented in this thesis provide a realistic set of tools to improve energy efficiency in current Wi-Fi networks

Energy-Aware Data Management on NUMA Architectures

The ever-increasing need for more computing and data processing power demands for a continuous and rapid growth of power-hungry data center capacities all over the world. As a first study in 2008 revealed, energy consumption of such data centers is becoming a critical problem, since their power consumption is about to double every 5 years. However, a recently (2016) released follow-up study points out that this threatening trend was dramatically throttled within the past years, due to the increased energy efficiency actions taken by data center operators. Furthermore, the authors of the study emphasize that making and keeping data centers energy-efficient is a continuous task, because more and more computing power is demanded from the same or an even lower energy budget, and that this threatening energy consumption trend will resume as soon as energy efficiency research efforts and its market adoption are reduced. An important class of applications running in data centers are data management systems, which are a fundamental component of nearly every application stack. While those systems were traditionally designed as disk-based databases that are optimized for keeping disk accesses as low a possible, modern state-of-the-art database systems are main memory-centric and store the entire data pool in the main memory, which replaces the disk as main bottleneck. To scale up such in-memory database systems, non-uniform memory access (NUMA) hardware architectures are employed that face a decreased bandwidth and an increased latency when accessing remote memory compared to the local memory. In this thesis, we investigate energy awareness aspects of large scale-up NUMA systems in the context of in-memory data management systems. To do so, we pick up the idea of a fine-grained data-oriented architecture and improve the concept in a way that it keeps pace with increased absolute performance numbers of a pure in-memory DBMS and scales up on NUMA systems in the large scale. To achieve this goal, we design and build ERIS, the first scale-up in-memory data management system that is designed from scratch to implement a data-oriented architecture. With the help of the ERIS platform, we explore our novel core concept for energy awareness, which is Energy Awareness by Adaptivity. The concept describes that software and especially database systems have to quickly respond to environmental changes (i.e., workload changes) by adapting themselves to enter a state of low energy consumption. We present the hierarchically organized Energy-Control Loop (ECL), which is a reactive control loop and provides two concrete implementations of our Energy Awareness by Adaptivity concept, namely the hardware-centric Resource Adaptivity and the software-centric Storage Adaptivity. Finally, we will give an exhaustive evaluation regarding the scalability of ERIS as well as our adaptivity facilities

The erodibility of fine sediment deposits in lowland chalk streams

PhDLowland chalk streams in the UK are experiencing increased deposition of fine sediment due to changes in land-use practices, channel modifications, and groundwater abstraction. The fine sediment is linked to benthic habitat degradation, the obstruction of surface-groundwater flow, and the storage of contaminants, such as nutrients and pesticides. Whilst research has been conducted on the provenance, transport, deposition, and storage of fine sediment in chalk streams, none has expressly investigated erosion. To help fill this gap in knowledge, a yearlong field survey was conducted in two reaches of the Frome-Piddle Catchment (Dorset) to quantify the erodibility of surficial fine sediment deposits. Sediment erodibility was measured in the field using a cohesive strength meter (CSM) and a shear vane. These measurements were paired with sediment cores for analysis of the physical, chemical and biological properties of the sediment. The large environmental dataset was analysed using a comprehensive suite of modern analytical techniques, including regression trees, linear regression, and mixed effects modelling. The results indicate that the erodibility of fine sediment varies significantly over time and within a stream reach due to variations in hydraulic conditions and sediment properties. Effective particle size and chlorophyll-a content were identified as the major sediment properties influencing CSM-derived erodibility, whereas root density was key for shear vane-derived strength. To date, the erosion thresholds generated by CSMs have been largely restricted to relative uses, and a calibration based on cohesive sediment is needed to permit their future incorporation into sediment transport models. This study developed an empirical calibration using laboratory experiments that estimated critical shear stress from CSM-derived erosion thresholds. By quantifying the erodibility of fine sediment deposits in chalk streams, and representing the erosion thresholds as critical shear stress, we can better gauge their local environmental impacts and help to inform models of fine sediment transpor