Model-driven service engineering in home telecare

Health care systems are highly dynamic not just due to developments and innovations in diagnosis and treatments, but also by virtue of emerging management techniques supported by modern information and communication technology. A multitude of stakeholders such as patients, nurses, general practitioners or social carers can be integrated by modeling complex interactions necessary for managing the provision and consumption of health care services. Furthermore, it is the availability of Service-oriented Architecture (SOA) that supports those integration efforts by enabling the flexible and reusable composition of autonomous, loosely-coupled and web-enabled software components. However, there is still the gap between SOA and predominantly business-oriented perspectives (e.g. business process models). The alignment of both views is crucial not just for the guided development of SOA but also for the sustainable evolution of holistic enterprise architectures. In this paper, we combine the Semantic Object Model (SOM) and the Business Process Modelling Notation (BPMN) towards a model-driven approach to service engineering. By addressing a business system in Home Telecare and deriving a business process model, which can eventually be controlled and executed by machines; in particular by composed web services, the full potential of a process-centric SOA is exploited.

The business case for transmedia

For transmedia to be acknowledged as worthy of investment by the business world, and even by those considering a career in development of transmedia creative products, there first needs to be established a business case for the concept. This chapter seeks to inform transmedia advocates about the concept of value and the ROI of transmedia more generally. While it is by no means a template or formula for measurement of value, it is a reminder to transmedia professionals and theorists, that intangible benefits are neither valueless nor unquantifiable. The chapter is divided into four sections: 1. Definitions of transmedia – concept and scope of transmedia, expressed in a manner that is intelligible for a business audience. 2. Value and cost – discussion of the terms from an economic perspective. 3. Audience interaction and collaborative content development – discussion of how feedback and engagement systems of transmedia have facilitated rich experiences which offer more than mere content and audience reach outputs. 4. ROI metrics for transmedia – measurable criteria for articulation of value to business investors.

Falling behind : business use of social media

Australians are turning onto social media in their droves - nearly 90 per cent of our citizenry are online and more than 50 per cent of the population has a Facebook account.

Faking it : how to kill a business through astroturfing on social media

There is no doubt about it the practice of astroturfing is lazy, misleading and potentially illegal public relations (PR). But on social media, astroturfing is not just lazy and misleading, it can be irresponsible and damaging.

Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows

This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

Organizational factors impacting on patient satisfaction : a cross sectional examination of service climate and linkages to nurses' effort and performance

Background Patient satisfaction is influenced by the setting in which patients are treated and the employees providing care. However, to date, limited research has explained how health care organizations or nurses influence patient satisfaction. Objectives The purpose of this study was to test the model that service climate would increase the effort and performance of nursing groups and, in turn, increase patient satisfaction. Method This study incorporated data from 156 nurses, 28 supervisors, and 171 patients. A cross-sectional design was utilized to examine the relationship between service climate, nurse effort, nurse performance and patient satisfaction. Structural equation modeling was conducted to test the proposed relationships. Results Service climate was associated with the effort that nurses directed towards technical care and extra-role behaviors. In turn, the effort that nurses exerted predicted their performance, as rated by their supervisors. Finally, task performance was a significant predictor of patient satisfaction. Conclusions This study suggests that both hospital management and nurses play a role in promoting patient satisfaction. By focusing on creating a climate for service, health care managers can improve nursing performance and patient satisfaction with care.

The impacts of FOREX fluctuations on construction business performance : an organisational capabilities perspective

Construction projects are a high risk business activity. When undertaking projects in an international context, it is further complicated by the risk of fluctuations in the foreign exchange rates (FOREX). Construction business performance is affected by these fluctuations. They affect progress and cause delays, which in turn create problems for subcontractors, namely cost overruns, disputes, arbitration, total abandonment and litigation. FOREX fluctuations also cause the price of raw materials to increase, leading the cost overruns. Managing FOREX risk is critical and past research have focused on the need for adequate insurance, careful planning and management, and foreign exchange futures hedging to overcome issues that have been caused by the FOREX risk. Analysis of FOREX risk in international construction business usually focused only on issues at the project level. There is currently lack of understanding of Organisational Capabilities (OC) to manage the impacts of FOREX risk, which when examined, are seen in isolation. This paper attempts to bridge the gap by discussing the impacts of FOREX fluctuations on the international construction business. The focus is on the OC perspective and the need to develop OC framework to mitigate the risk in sustaining construction business performance.

Modeling nitrous oxide emissions from irrigated agriculture : testing DayCent with high-frequency measurements

A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.

Modeling and sensorless direct torque and flux control of a dual-airgap axial flux permanent-magnet machine with field-weakening operation

This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.

Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

Hyperbranched polymer-gold nanoparticle assemblies : role of polymer architecture in hybrid assembly formation and SERS activity

Plasmonic gold nano-assemblies that self-assemble with the aid of linking molecules or polymers have the potential to yield controlled hierarchies of morphologies and consequently result in materials with tailored optical (e.g. localized surface plasmon resonances (LSPR)) and spectroscopic properties (e.g. surface enhanced Raman scattering (SERS)). Molecular linkers that are structurally well-defined are promising for forming hybrid nano-assemblies which are stable in aqueous solution and are increasingly finding application in nanomedicine. Despite much ongoing research in this field, the precise role of molecular linkers in governing the morphology and properties of the hybrid nano-assemblies remains unclear. Previously we have demonstrated that branched linkers, such as hyperbranched polymers, with specific anchoring end groups can be successfully employed to form assemblies of gold NPs demonstrating near-infrared SPRs and intense SERS scattering. We herein introduce a tailored polymer as a versatile molecular linker, capable of manipulating nano-assembly morphologies and hot-spot density. In addition, this report explores the role of the polymeric linker architecture, specifically the degree of branching of the tailored polymer in determining the formation, morphology and properties of the hybrid nano-assemblies. The degree of branching of the linker polymer, in addition to the concentration and number of anchoring groups, is observed to strongly influence the self-assembly process. The assembly morphology shifts primarily from 1D-like chains to 2D plates and finally to 3D-like globular structures, with increase in degree of branching. Insights have been gained into how the morphology influences the SERS performance of these nano-assemblies with respect to hot-spot density. These findings supplement the understanding of the morphology determining nano-assembly formation and pave the way for the possible application of these nano-assemblies as SERS bio-sensors for medical diagnostics.

Modeling and analysis of a novel variable-speed cage induction generator

This paper introduces a novel cage induction generator and presents a mathematical model, through which its behavior can be accurately predicted. The proposed generator system employs a three-phase cage induction machine and generates single-phase and constant-frequency electricity at varying rotor speeds without an intermediate inverter stage. The technique uses any one of the three stator phases of the machine as the excitation winding and the remaining two phases, which are connected in series, as the power winding. The two-series-connected-and-one-isolated (TSCAOI) phase winding configuration magnetically decouples the two sets of windings, enabling independent control. Electricity is generated through the power winding at both sub- and super-synchronous speeds with appropriate excitation to the isolated single winding at any frequency of generation. A dynamic mathematical model, which accurately predicts the behavior of the proposed generator, is also presented and implemented in MATLAB/Simulink. Experimental results of a 2-kW prototype generator under various operating conditions are presented, together with theoretical results, to demonstrate the viability of the TSCAOI power generation. The proposed generator is simple and capable of both storage and retrieval of energy through its excitation winding and is expected to be suitable for applications, such as small wind turbines and microhydro systems.

Beyond tasks and gateways: discovering BPMN models with subprocesses, boundary events and activity markers

Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

A transcriptomic analysis of striped catfish (Pangasianodon hypophthalmus) in response to salinity adaptation: De novo assembly, gene annotation and marker discovery

The striped catfish (Pangasianodon hypophthalmus) culture industry in the Mekong Delta in Vietnam has developed rapidly over the past decade. The culture industry now however, faces some significant challenges, especially related to climate change impacts notably from predicted extensive saltwater intrusion into many low topographical coastal provinces across the Mekong Delta. This problem highlights a need for development of culture stocks that can tolerate more saline culture environments as a response to expansion of saline water-intruded land. While a traditional artificial selection program can potentially address this need, understanding the genomic basis of salinity tolerance can assist development of more productive culture lines. The current study applied a transcriptomic approach using Ion PGM technology to generate expressed sequence tag (EST) resources from the intestine and swim bladder from striped catfish reared at a salinity level of 9 ppt which showed best growth performance. Total sequence data generated was 467.8 Mbp, consisting of 4,116,424 reads with an average length of 112 bp. De novo assembly was employed that generated 51,188 contigs, and allowed identification of 16,116 putative genes based on the GenBank non-redundant database. GO annotation, KEGG pathway mapping, and functional annotation of the EST sequences recovered with a wide diversity of biological functions and processes. In addition, more than 11,600 simple sequence repeats were also detected. This is the first comprehensive analysis of a striped catfish transcriptome, and provides a valuable genomic resource for future selective breeding programs and functional or evolutionary studies of genes that influence salinity tolerance in this important culture species.

Self assembly of plasmonic core-satellite nano-assemblies mediated by hyperbranched polymer linkers

The morphology of plasmonic nano-assemblies has a direct influence on optical properties, such as localised surface plasmon resonance (LSPR) and surface enhanced Raman scattering (SERS) intensity. Assemblies with core-satellite morphologies are of particular interest, because this morphology has a high density of hot-spots, while constraining the overall size. Herein, a simple method is reported for the self-assembly of gold NPs nano-assemblies with a core-satellite morphology, which was mediated by hyperbranched polymer (HBP) linkers. The HBP linkers have repeat units that do not interact strongly with gold NPs, but have multiple end-groups that specifically interact with the gold NPs and act as anchoring points resulting in nano-assemblies with a large (~48 nm) core surrounded by smaller (~15 nm) satellites. It was possible to control the number of satellites in an assembly which allowed optical parameters such as SPR maxima and the SERS intensity to be tuned. These results were found to be consistent with finite-difference time domain (FDTD) simulations. Furthermore, the multiplexing of the nano-assemblies with a series of Raman tag molecules was demonstrated, without an observable signal arising from the HBP linker after tagging. Such plasmonic nano-assemblies could potentially serve as efficient SERS based diagnostics or biomedical imaging agents in nanomedicine.