Implementing Network Protocols as Distributed Logic Programs

Declarative networking [2, 4, 3, 1] is an application of database query-language and processing techniques to the domain of networking. Declarative networking is based on the observation that network protocols deal at their core with computing and maintaining distributed state (e.g., routes, sessions, performance statistics) according to basic information locally available at each node (e.g., neighbor tables, link measurements, local clocks) while enforcing constraints such as local routing policies. Recursive query languages studied in the deductive database literature [6] are a natural fit for expressing the relationship between base data, derived data, and the associated constraints. Simple extensions to these languages and their implementations enable the natural expression and efficient execution of network protocols. Declarative networking aims to accelerate the process of specifying, implementing, experimenting with and evolving designs for network architectures. Declarative networking can reduce program sizes of distributed protocols by orders of magnitude relative to traditional approaches. In addition to serving as a platform for rapid prototyping of network protocols, declarative networking also open up opportunities for automatic protocol optimization and hybridization, program checking and debugging. This paper presents an introduction to declarative networking using a simple routing protocol example. For more details on declarative networking related projects, refer to the NetDB@Penn website [5], and the RapidNet [7] declarative networking engine

On the correction of “old” omitted citations by bibliometric databases

Omitted citations – i.e., missing links between a cited paper and the corresponding citing papers – are the main consequence of several bibliometric-database errors. To reduce these errors, databases may undertake two actions: (i) improving the control of the (new) papers to be indexed, i.e., limiting the introduction of “new” dirty data, and (ii) detecting and correcting errors in the papers already indexed by the database, i.e., cleaning “old” dirty data. The latter action is probably more complicated, as it requires the application of suitable error-detection procedures to a huge amount of data. Based on an extensive sample of scientific papers in the Engineering-Manufacturing field, this study focuses on old dirty data in the Scopus and WoS databases. To this purpose, a recent automated algorithm for estimating the omitted-citation rate of databases is applied to the same sample of papers, but in three different-time sessions. A database’s ability to clean the old dirty data is evaluated considering the variations in the omitted-citation rate from session to session. The major outcomes of this study are that: (i) both databases slowly correct old omitted citations, and (ii) a small portion of initially corrected citations can surprisingly come off from databases over time

The local evaluation of Knutsford’s Healthy Living Network: January 2006 – December 2006

This was an exploratory study designed to evaluate the Knutsford Healthy Living Network (KHLN), one of many Healthy Living Centres (HLC) in the UK. The HLC initiative aims to ensure people can achieve their optimum state of health and well-being. The project report aims to establish the reach of KHLN services by monitoring the level of service usage using a database designed to capture service activity

A Deep Learning Approach to Examine Ischemic ST Changes in Ambulatory ECG Recordings.

Patients with suspected acute coronary syndrome (ACS) are at risk of transient myocardial ischemia (TMI), which could lead to serious morbidity or even mortality. Early detection of myocardial ischemia can reduce damage to heart tissues and improve patient condition. Significant ST change in the electrocardiogram (ECG) is an important marker for detecting myocardial ischemia during the rule-out phase of potential ACS. However, current ECG monitoring software is vastly underused due to excessive false alarms. The present study aims to tackle this problem by combining a novel image-based approach with deep learning techniques to improve the detection accuracy of significant ST depression change. The obtained convolutional neural network (CNN) model yields an average area under the curve (AUC) at 89.6% from an independent testing set. At selected optimal cutoff thresholds, the proposed model yields a mean sensitivity at 84.4% while maintaining specificity at 84.9%

Intelligent and adaptive tutoring for active learning and training environments

Active learning facilitated through interactive and adaptive learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a Web-based e-learning environment that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. We propose knowledge-level interaction and adaptive feedback and guidance as central features. We discuss these features and evaluate the effectiveness of this Web-based environment, focusing on different aspects of learning behaviour and tool usage. Motivation, acceptance of the approach, learning organisation and actual tool usage are aspects of behaviour that require different evaluation techniques to be used

An active learning and training environment for database programming

Active learning facilitated through interactive, self-controlled learning environments differs substantially from traditional instructor-oriented, classroom-based teaching. We present a tool for database programming that integrates knowledge learning and skills training. How these tools are used most effectively is still an open question. Therefore, we discuss analysis and evaluation of these Web-based environments focusing on different aspects of learning behaviour and tool usage. Motivation, acceptance of the learning approach, learning organisation and actual tool usage are aspects of behaviour that require different techniques to be used

Baseline utilisation of specialist disability services in Ireland. ESRI Working Paper No.644 December 2019

The objective of this paper is to analyse the data on specialist disability services available in Ireland. The paper provides a baseline utilisation profile of selected services which can be used to project future service demand and expenditure. The limitations of the currently available data in providing a comprehensive picture of specialist disability services in Ireland are also outlined

The Validation of Speech Corpora

1.2 Intended audience........................

FOCUS on technology‐supported learning in further education

This paper introduces FOCUS, a ‘one‐stop shop’ for technology‐supported learning resources designed and developed by a consortium of higher and further education partners. It reports on an investigation of the issues surrounding the adaptation of this HE‐orientated resource to an FE context. This involved piloting FOCUS with FE staff to assess its suitability. The issues raised by this process are discussed and general implications for the adaptation of generic HE resources to the FE sector are identified