Simulation analysis of an adjusted gravity model for hospital admissions robust to incomplete data.

BACKGROUND: Gravity models are often hard to apply in practice due to their data-hungry nature. Standard implementations of gravity models require that data on each variable is available for each supply node. Since these model types are often applied in a competitive context, data availability of specific variables is commonly limited to a subset of supply nodes. METHODS: This paper introduces a methodology that accommodates the use of variables for which data availability is incomplete, developed for a health care context, but more broadly applicable. The study uses simulated data to evaluate the performance of the proposed methodology in comparison with a conventional approach of dropping variables from the model. RESULTS: It is shown that the proposed methodology is able to improve overall model accuracy compared to dropping variables from the model, and that model accuracy is considerably improved within the subset of supply nodes for which data is available, even when that availability is sparse. CONCLUSION: The proposed methodology is a viable approach to improve the performance of gravity models in a competitive health care context, where data availability is limited, and especially where a the supply nodes with complete data are most relevant for the practitioner.

Optimising orbit counting of arbitrary order by equation selection.

BACKGROUND: Graphlets are useful for bioinformatics network analysis. Based on the structure of Hocevar and Demsar's ORCA algorithm, we have created an orbit counting algorithm, named Jesse. This algorithm, like ORCA, uses equations to count the orbits, but unlike ORCA it can count graphlets of any order. To do so, it generates the required internal structures and equations automatically. Many more redundant equations are generated, however, and Jesse's running time is highly dependent on which of these equations are used. Therefore, this paper aims to investigate which equations are most efficient, and which factors have an effect on this efficiency. RESULTS: With appropriate equation selection, Jesse's running time may be reduced by a factor of up to 2 in the best case, compared to using randomly selected equations. Which equations are most efficient depends on the density of the graph, but barely on the graph type. At low graph density, equations with terms in their right-hand side with few arguments are more efficient, whereas at high density, equations with terms with many arguments in the right-hand side are most efficient. At a density between 0.6 and 0.7, both types of equations are about equally efficient. CONCLUSIONS: Our Jesse algorithm became up to a factor 2 more efficient, by automatically selecting the best equations based on graph density. It was adapted into a Cytoscape App that is freely available from the Cytoscape App Store to ease application by bioinformaticians.

Efficiently counting all orbits of graphlets of any order in a graph using autogenerated equations.

Motivation: Graphlets are a useful tool to determine a graph's small-scale structure. Finding them is exponentially hard with respect to the number of nodes in each graphlet. Therefore, equations can be used to reduce the size of graphlets that need to be enumerated to calculate the number of each graphlet touching each node. Hocevar and Demsar first introduced such equations, which were derived manually, and an algorithm that uses them, but only graphlets with four or five nodes can be counted this way. Results: We present a new algorithm for orbit counting, which is applicable to graphlets of any order. This algorithm uses a tree structure to simplify finding orbits, and stabilizers and symmetry-breaking constraints to ensure correctness. This method gives a significant speedup compared to a brute force counting method and can count orbits beyond the capacity of other available tools. Availability and implementation: An implementation of the algorithm can be found at https://github.com/biointec/jesse. Contact: pieter.audenaert@ugent.be.

A Cytoscape app for motif enumeration with ISMAGS.

Summary: We present a Cytoscape app for the ISMAGS algorithm, which can enumerate all instances of a motif in a graph, making optimal use of the motif's symmetries to make the search more efficient. The Cytoscape app provides a handy interface for this algorithm, which allows more efficient network analysis. Availability and Implementation: The Cytoscape app for ISMAGS can be freely downloaded from the Cytoscape App store http://apps.cytoscape.org/apps/ismags. Source code and documentation for ISMAGS are available at https://github.com/biointec/ismags. Source code and documentation for the Cytoscape app are available at https://gitlab.psb.ugent.be/thpar/ISMAGS_Cytoscape. Contacts: Pieter.Audenaert@intec.ugent.be or Yves.VanDePeer@psb.vib-ugent.be Supplementary information: Supplementary data are available at Bioinformatics online.

ONU power saving modes in next generation optical access networks: progress, efficiency and challenges.

The optical network unit (ONU), installed at a customer's premises, accounts for about 60% of power in current fiber-to-the-home (FTTH) networks. We propose a power consumption model for the ONU and evaluate the ONU power consumption in various next generation optical access (NGOA) architectures. Further, we study the impact of the power savings of the ONU in various low power modes such as power shedding, doze and sleep.

Worldwide electricity consumption of communication networks.

There is a growing research interest in improving the energy efficiency of communication networks. In order to assess the impact of introducing new energy efficient technologies, an up-to-date estimate for the global electricity consumption in communication networks is needed. In this paper we consider the use phase electricity consumption of telecom operator networks, office networks and customer premises equipment. Our results show that the network electricity consumption is growing fast, at a rate of 10 % per year, and its relative contribution to the total worldwide electricity consumption has increased from 1.3% in 2007 to 1.8% in 2012. We estimate the worldwide electricity consumption of communication networks will exceed 350 TWh in 2012.

A construction heuristic for the capacitated Steiner tree problem.

Many real-life problems boil down to a variant of the Minimum Steiner Tree Problem (STP). In telecommunications, Fiber-To-The-Home (FTTH) houses are clustered so they can be connected with fiber as cost-efficiently as possible. The cost calculation of a fiber installment can be formulated as a capacitated STP. Often, STP variants are solved with integer linear programs, which provide excellent solutions, though the running time costs increase quickly with graph size. Some geographical areas require graphs of over 20000 nodes-typically unattainable for integer linear programs. This paper presents an alternative approach. It extends the shortest path heuristic for the STP to a new heuristic that can construct solutions for the capacitated STP: the Capacitated Shortest Path Heuristic (CSPH). It is straightforward to implement, allowing many extensions. In experiments on realistic telecommunications datasets, CSPH finds solutions on average in time O(|V|2), quadratic in the number of nodes, making it possible to solve 50000 node graphs in under a minute.

Bringing eCare platforms to the market.

Due to changes in the demographic situation of most Western European countries, interest in Information and Communication Technologies (ICT)-supported care services is growing fast. eCare services that foster better care information exchange, social involvement, lifestyle monitoring services, etc., offered via ICT platforms, integrated in the homes of the elderly are believed to be cost-effective. Additionally, they could lead to an increased quality of life of both care receiver and (in)formal caregiver. Currently, adoption and integration of these eCare platforms (eCPs) is slowed down by several barriers such as unclear added value, a lack of regulations, or lack of sustainable financial models. In this work, the added value of eCPs is identified for the several involved key actors such as the care receiver, the (in)formal care providers, and the home care organizations. In a second step, several go-to-market strategies are formulated. Because the gap between the current way of providing home care and providing home care supported by a fully integrated eCP seems too big to bridge in one effort, a migration path is provided for stepwise integration and adoption of eCPs in the current way of home care provisioning.

An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.

Graphlets are small subgraphs, usually containing up to five vertices, that can be found in a larger graph. Identification of the graphlets that a vertex in an explored graph touches can provide useful information about the local structure of the graph around that vertex. Actually finding all graphlets in a large graph can be time-consuming, however. As the graphlets grow in size, more different graphlets emerge and the time needed to find each graphlet also scales up. If it is not needed to find each instance of each graphlet, but knowing the number of graphlets touching each node of the graph suffices, the problem is less hard. Previous research shows a way to simplify counting the graphlets: instead of looking for the graphlets needed, smaller graphlets are searched, as well as the number of common neighbors of vertices. Solving a system of equations then gives the number of times a vertex is part of each graphlet of the desired size. However, until now, equations only exist to count graphlets with 4 or 5 nodes. In this paper, two new techniques are presented. The first allows to generate the equations needed in an automatic way. This eliminates the tedious work needed to do so manually each time an extra node is added to the graphlets. The technique is independent on the number of nodes in the graphlets and can thus be used to count larger graphlets than previously possible. The second technique gives all graphlets a unique ordering which is easily extended to name graphlets of any size. Both techniques were used to generate equations to count graphlets with 4, 5 and 6 vertices, which extends all previous results. Code can be found at https://github.com/IneMelckenbeeck/equation-generator and https://github.com/IneMelckenbeeck/graphlet-naming.

Evaluating the Economic Impact of Smart Care Platforms: Qualitative and Quantitative Results of a Case Study.

BACKGROUND: In response to the increasing pressure of the societal challenge because of a graying society, a gulf of new Information and Communication Technology (ICT) supported care services (eCare) can now be noticed. Their common goal is to increase the quality of care while decreasing its costs. Smart Care Platforms (SCPs), installed in the homes of care-dependent people, foster the interoperability of these services and offer a set of eCare services that are complementary on one platform. These eCare services could not only result in more quality care for care receivers, but they also offer opportunities to care providers to optimize their processes. OBJECTIVE: The objective of the study was to identify and describe the expected added values and impacts of integrating SCPs in current home care delivery processes for all actors. In addition, the potential economic impact of SCP deployment is quantified from the perspective of home care organizations. METHODS: Semistructured and informal interviews and focus groups and cocreation workshops with service providers, managers of home care organizations, and formal and informal care providers led to the identification of added values of SCP integration. In a second step, process breakdown analyses of home care provisioning allowed defining the operational impact for home care organization. Impacts on 2 different process steps of providing home care were quantified. After modeling the investment, an economic evaluation compared the business as usual (BAU) scenario versus the integrated SCP scenario. RESULTS: The added value of SCP integration for all actors involved in home care was identified. Most impacts were qualitative such as increase in peace of mind, better quality of care, strengthened involvement in care provisioning, and more transparent care communication. For home care organizations, integrating SCPs could lead to a decrease of 38% of the current annual expenses for two administrative process steps namely, care rescheduling and the billing for care provisioning. CONCLUSIONS: Although integrating SCP in home care processes could affect both the quality of life of the care receiver and informal care giver, only scarce and weak evidence was found that supports this assumption. In contrast, there exists evidence that indicates the lack of the impact on quality of life of the care receiver while it increases the cost of care provisioning. However, our cost-benefit quantification model shows that integrating SCPs in home care provisioning could lead to a considerable decrease of costs for care administrative tasks. Because of this cost decreasing impact, we believe that the integration of SCPs will be driven by home care organizations instead of the care receivers themselves.

The Index-based Subgraph Matching Algorithm with General Symmetries (ISMAGS): exploiting symmetry for faster subgraph enumeration.

Subgraph matching algorithms are used to find and enumerate specific interconnection structures in networks. By enumerating these specific structures/subgraphs, the fundamental properties of the network can be derived. More specifically in biological networks, subgraph matching algorithms are used to discover network motifs, specific patterns occurring more often than expected by chance. Finding these network motifs yields information on the underlying biological relations modelled by the network. In this work, we present the Index-based Subgraph Matching Algorithm with General Symmetries (ISMAGS), an improved version of the Index-based Subgraph Matching Algorithm (ISMA). ISMA quickly finds all instances of a predefined motif in a network by intelligently exploring the search space and taking into account easily identifiable symmetric structures. However, more complex symmetries (possibly involving switching multiple nodes) are not taken into account, resulting in superfluous output. ISMAGS overcomes this problem by using a customised symmetry analysis phase to detect all symmetric structures in the network motif subgraphs. These structures are then converted to symmetry-breaking constraints used to prune the search space and speed up calculations. The performance of the algorithm was tested on several types of networks (biological, social and computer networks) for various subgraphs with a varying degree of symmetry. For subgraphs with complex (multi-node) symmetric structures, high speed-up factors are obtained as the search space is pruned by the symmetry-breaking constraints. For subgraphs with no or simple symmetric structures, ISMAGS still reduces computation times by optimising set operations. Moreover, the calculated list of subgraph instances is minimal as it contains no instances that differ by only a subgraph symmetry. An implementation of the algorithm is freely available at https://github.com/mhoubraken/ISMAGS.