INTRODUCTION Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision. METHODS AND ANALYSIS Phase I: A coh...

Casemix refers to a mix of patients classified in some way. It describes a system which groups patients by predetermined factors into clinically meaningful and resource homogenous groups to describe the hospital or health service product (a measure of output). A number of patient classification (casemix) systems have been developed for various purposes. The casemix system used by Australian acu...

Resource Utilization Groups, Version III (RUG-III) is a case-mix system developed in the USA for classification of long-term care residents. This paper examines the validity and reliability of an adapted 22-group version of RUG-III (RUG-III/22) for use in long-term care facilities in Finland. Finnish cost weights for RUG-III/22 groups are calculated and different methods for their computation a...

The development of robust object-oriented classification methods suitable for medium to high resolution satellite imagery provides a valid alternative to ‘traditional’ pixel-based methods. This paper compares the results of an object-oriented classification to a supervised pixel-based classification for mapping land cover in the tropical north of the Northern Territory. The object-oriented appr...

The Faceted Classification Scheme (FCS) ODP is a Reengineering ODP that transforms a non-ontological resource from the field of Library and Information Science, also known as Faceted Classification Scheme, into an ontological resource. The ontological resource corresponds to an OWL DL model that results from a specific application of the Normalisation ODP [4] [2] based on a series of (a) alignm...

Land use is being considered as an element in determining land change studies, environmental planning and natural resource applications. The Earth’s surface Study by remote sensing has many benefits such as, continuous acquisition of data, broad regional coverage, cost effective data, map accurate data, and large archives of historical data. To study land use / cover, remote sensing as an effic...

Multi-dimensional packet classification is a key function for networking applications in high-speed routers. Although a multitude of research has explored this area, efficient packet classification that supports large rule sets at line rate remains challenging. This paper presents a scalable pipeline architecture, named BiConOLP, for line rate packet classification on FPGAs. We study the proble...

The resource space model (RSM) is a semantic data model based on orthogonal classification semantics for efficiently managing various resources in the future interconnection environment. This paper extends the RSM in theory by formalizing the resource space, investigating its characteristics from the perspective of set theory, defining the resource space schema and developing its normal forms. ...

We consider a model of resource dependence where only the seller knows the resource reserve. The model captures phenomena such as trust in the relationship and “bribing” for continuation through generous supplies. It also explains supply shocks in equilibrium: privately informed sellers have incentives to reveal their types too late through a supply disruption after which their exploit the cons...

Multilingual deep neural network (DNN) has been widely used in low-resource automatic speech recognition (ASR) in order to balance the rich-resource and low-resource speech recognition or to build the low-resource ASR system quickly. Inspired by the idea of using multilingual DNN for ASR, we use a “multilingual” DNN (Multi-DNN) for music genre classification. However, we do not have “multilingu...