Search

Natural language processing technology has made significant progress in recent years, fuelled by increasingly powerful general language models. This has also inspired a sizeable body of work targeted specifically towards the educational domain, where the creation of questions (both for assessment and practice) is a laborious/expensive effort. Thus, automatic Question-Generation (QG) solutions have been proposed and studied. Yet, according to a recent survey of the educational QG community's progress, a common baseline dataset unifying multiple domains and question forms (e.g., multiple choice vs. fill-the-gap), including readily available baseline models to compare against, is largely missing. This is the gap we aim to fill with this paper. In particular, we introduce a high-quality dataset in the educational domain, containing over 3,000 entries, comprising (i) multiple-choice questions, (ii) the corresponding answers (including distractors), and (iii) associated passages from the course material used as sources for the questions. Each question is phrased in two forms, normal and cloze (i.e., fill-the-gap), and correct answers are linked to source documents with sentence-level annotations. Thus, our versatile dataset can be used for both question and distractor generation, as well as to explore new challenges such as question format conversion. Furthermore, 903 questions are accompanied by their cognitive complexity level as per Bloom's taxonomy. All questions have been generated by educational experts rather than crowd workers to ensure they are maintaining educational and learning standards. Our analysis and experiments suggest distinguishable differences between our dataset and commonly used ones for question generation for educational purposes. We believe this new dataset can serve as a valuable resource for research and evaluation in the educational domain. The dataset and baselines are made available to support further research in question generation for education (https://github.com/hadifar/question-generation).

Smart grids collect large volumes of smart meter data in the form of time series, or so-called load patterns. We outline the applications that benefit from analyzing this data (ranging from customer segmentation to operational system planning), and propose two-stage load pattern clustering. The first stage is performed per individual user and identifies the various typical daily power usage patterns (s)he exhibits. The second stage takes those typical user patterns as input to group users that are similar. To improve scalability, we use fast wavelet transformation (FWT) of the time series data, which reduces the dimensionality of the feature space where the clustering algorithm operates (i.e., from ${N}$ data points in the time domain to log ${N}$ ). Another qualitative benefit of FWT is that patterns that are identical in shape, but just differ in a (typically small) time shift still end up in the same cluster. Furthermore, we use ${g}$ -means instead of ${k}$ -means as the clustering algorithm. Our comprehensive set of experiments analyzes the impact of using FWT versus time-domain features, and ${g}$ - versus ${k}$ -means, to conclude that in terms of cluster quality metrics our system is comparable to state-of-the-art methods, while being more scalable (because of the dimensionality reduction).

We address the dimensioning of infrastructure, comprising both network and server resources, for large-scale decentralized distributed systems such as grids or clouds. We design the resulting grid/cloud to be resilient against network link or server failures. To this end, we exploit relocation: Under failure conditions, a grid job or cloud virtual machine may be served at an alternate destination (i.e., different from the one under failure-free conditions). We thus consider grid/cloud requests to have a known origin, but assume a degree of freedom as to where they end up being served, which is the case for grid applications of the bag-of-tasks (BoT) type or hosted virtual machines in the cloud case. We present a generic methodology based on integer linear programming (ILP) that: 1) chooses a given number of sites in a given network topology where to install server infrastructure; and 2) determines the amount of both network and server capacity to cater for both the failure-free scenario and failures of links or nodes. For the latter, we consider either failure-independent (FID) or failure-dependent (FD) recovery. Case studies on European-scale networks show that relocation allows considerable reduction of the total amount of network and server resources, especially in sparse topologies and for higher numbers of server sites. Adopting a failure-dependent backup routing strategy does lead to lower resource dimensions, but only when we adopt relocation (especially for a high number of server sites): Without exploiting relocation, potential savings of FD versus FID are not meaningful.

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium, price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

The evolution toward grid and cloud computing as observed for over a decennium illustrates the crucial role played by (optical) networks in supporting today's applications. In this paper, we start from an overview of the challenging applications in both academic (further referred to as scientific), enterprise (business) and nonprofessional user (consumer) domains. They pose novel challenges, calling for efficient interworking of IT resources, for both processing and storage, as well as the network that interconnects them and provides access to their users. We outline those novel applications' requirements, including sheer performance attributes (which will determine the quality as perceived by end users of the cloud applications), as well as the ability to adapt to changing demands (usually referred to as elasticity) and possible failures (i.e., resilience). In outlining the foundational concepts that provide the building blocks for grid/cloud solutions that meet the stringent application requirements we highlight, a prominent role is played by optical networking. The pieces of the solution studied in this respect span the optical transport layer as well as mechanisms located in higher layers (e.g., anycast routing, virtualization) and their interworking (e.g., through appropriate control plane extensions and middleware). Based on this study, we conclude by identifying challenges and research opportunities that can enable future-proof optical cloud systems (e.g., pushing the virtualization paradigms to optical networks).

Optical packet switching (OPS) has been proposed as a strong candidate for future metro networks. This paper assesses the viability of an OPS-based ring architecture as proposed within the research project DAVID (Data And Voice Integration on DWDM), funded by the European Commission through the Information Society Technologies (IST) framework. Its feasibility is discussed from a physical-layer point of view, and its limitations in size are explored. Through dimensioning studies, we show that the proposed OPS architecture is competitive with respect to alternative metropolitan area network (MAN) approaches, including synchronous digital hierarchy, resilient packet rings (RPR), and star-based Ethernet. Finally, the proposed OPS architectures are discussed from a logical performance point of view, and a high-quality scheduling algorithm to control the packet-switching operations in the rings is explained.

In this paper, promising technologies and a network architecture are presented for future optical packet switched networks. The overall network concept is presented and the major choices are highlighted and compared with alternative solutions. Both long and shorter term approaches are considered, as well as both the wide-area network and multiple-area networks parts of the network. The results presented in this paper were developed in the frame of the research project DAVID (Data And Voice Integration over DWDM) project, funded by the European Commission through the IST-framework.

The explosive growth of data traffic-for example, due to the popularity of the Internet-poses important emerging network requirements on today's telecommunication networks. This paper describes how core networks will evolve to optical transport networks (OTNs), which are optimized for the transport of data traffic, resulting in an IP-directly-over-OTN paradigm. Special attention is paid to the survivability of such data-centric optical networks. This becomes increasingly crucial since more and more traffic is multiplexed onto a single fiber (e.g., 160/spl times/10 Gb/s), implying that a single cable cut can affect incredible large traffic volumes. In particular, this paper is tackling multilayer survivability problems, since a data-centric optical network consists of at least an IP and optical layer. In practice, this means that the questions "in which layer or layers should survivability be provided?" and "if multiple layers are chosen for this purpose, then how should this functionality in these layers be coordinated?" have to be answered. In addition to a theoretical study, some case studies are presented in order to illustrate the relevance of the described issues and to help in strategic planning decisions. Two case studies are studying the problem from a capacity viewpoint. Another case study presents simulations from a timing/throughput performance viewpoint.

In recent years, telecommunication networks have faced explosive (IP) traffic growth. As traffic keeps growing, network reliability gains more and more importance. This article investigates to which extent switched connections and fast connection provisioning, typical for intelligent optical networks (IONs), can be used to provide resilience in an IP-over-optical multilayer network scenario. This solution, based on transport network flexibility, is compared with more traditional static multilayer resilience schemes in terms of cost (capacity) requirements and operational (dis)advantages.

The aim of this special issue was to collect from academic and industrial players, tutorials and surveys related to the latest smart grid and energy related technologies and architectures. Contributions on major developments and updates on smart grid systems are considered. We received a total of 15 submissions from which five were finally accepted for this special issue. The papers span from smart grid communications to building energy efficiency, smart metering, information management, and co-simulation of power and communication systems. Each of the five article is briefly summarized.