On MIMO Radar Subarrayed Transmit Beamforming

Multiple-input-multiple-output (MIMO) radar schemes whereby the transmit array is partitioned into subarrays have recently been proposed in the literature to combine advantages of phased array and MIMO radar technology. In this work, we utilize this architecture to significantly simplify a transmit procedure in which the covariance matrix across the MIMO radar array is optimized to improve the Cramer-Rao bound (CRB) on target parameter estimation. The MIMO effective array for regular subarrayed transmit apertures is studied, and necessary conditions to obtain a filled effective aperture are presented, which is important for maintaining nonambiguous, low sidelobe beampatterns. The performance of the subarrayed transmit approach is evaluated in terms of the CRB on target parameter estimation, and the optimisation of the beamformer applied to the subarrays to minimize the CRB is considered. The subarrayed transmit scheme is found to have a CRB which is suboptimal to the full diversity transmission, as expected, but is solvable in a small fraction of the time using an iterative beamspace algorithm developed here.

Software-defined sphere decoding for FPGA-based MIMO detection

Sphere Decoding (SD) is a highly effective detection technique for Multiple-Input Multiple-Output (MIMO) wireless communications receivers, offering quasi-optimal accuracy with relatively low computational complexity as compared to the ideal ML detector. Despite this, the computational demands of even low-complexity SD variants, such as Fixed Complexity SD (FSD), remains such that implementation on modern software-defined network equipment is a highly challenging process, and indeed real-time solutions for MIMO systems such as 4 4 16-QAM 802.11n are unreported. This paper overcomes this barrier. By exploiting large-scale networks of fine-grained softwareprogrammable processors on Field Programmable Gate Array (FPGA), a series of unique SD implementations are presented, culminating in the only single-chip, real-time quasi-optimal SD for 44 16-QAM 802.11n MIMO. Furthermore, it demonstrates that the high performance software-defined architectures which enable these implementations exhibit cost comparable to dedicated circuit architectures.

Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

An exploration of the attitudes and strategic responses of soleproprietor micro-enterprises in adopting information and communication technology

This article analyses longitudinal case-based research exploring the attitudes and strategic responses of micro-enterprise owners in adopting information and communication technology (ICT). In so doing, it contributes to the limited literature on micro-enterprise ICT adoption, with a particular focus on sole proprietors. It provides a basis for widening the theoretical base of the literature pertaining to ICT adoption on two levels. First, a framework is developed which integrates the findings to illustrate the relationships between attitudes towards ICT adoption, endogenous and exogenous influencers of these attitudes and subsequent strategic response in ICT adoption. Second, building upon this framework the article reveals the unique challenges, opportunities and implications of ICT adoption for sole-proprietor micro-enterprises. © The Author(s) 2012

Visualising Textual Knowledge about Risks to Aid Risk Communication

This paper demonstrates a potential application for latent semantic analysis and similar techniques in visualising the differences between two levels of knowledge about a risk issue. The HIV/AIDS risk issue will be examined and the semantic clusters of key words in a technical corpora derived from specific literature about HIV/AIDS will be compared with the semantic clusters of those in more general corpora. It is hoped that these comparisons will create a fast and efficient complementary approach to the articulation of mental models of risk issues that could be used to target possible inconsistencies between expert and lay mental models.

A defeasible reasoning model of inductive concept learning from examples and communication

This paper introduces a logical model of inductive generalization, and specifically of the machine learning task of inductive concept learning (ICL). We argue that some inductive processes, like ICL, can be seen as a form of defeasible reasoning. We define a consequence relation characterizing which hypotheses can be induced from given sets of examples, and study its properties, showing they correspond to a rather well-behaved non-monotonic logic. We will also show that with the addition of a preference relation on inductive theories we can characterize the inductive bias of ICL algorithms. The second part of the paper shows how this logical characterization of inductive generalization can be integrated with another form of non-monotonic reasoning (argumentation), to define a model of multiagent ICL. This integration allows two or more agents to learn, in a consistent way, both from induction and from arguments used in the communication between them. We show that the inductive theories achieved by multiagent induction plus argumentation are sound, i.e. they are precisely the same as the inductive theories built by a single agent with all data. © 2012 Elsevier B.V.

Identifying functional stakeholder clusters to maximise communication for the ecosystem approach to fisheries management

Interaction with ecological models can improve stakeholder participation in fisheries management. Problems exist in efficiently communicating outputs to stakeholders and an objective method of structuring stakeholder differences is lacking. This paper aims to inform the design of a multi-user communication interface for fisheries management by identifying functional stakeholder groups. Intuitive categorisation of stakeholders, derived from survey responses, is contrasted with an Evidence-Based method derived from analysis of stakeholder literature. Intuitive categorisation relies on interpretation and professional judgement when categorising stakeholders among conventional stakeholder groups. Evidence-Based categorisation quantitatively characterises each stakeholder with a vector of four management objective interest-strength values (Yield, Employment, Profit and Ecosystem Preservation). Survey respondents agreed little in forming intuitive groups and the groups were poorly defined and heterogeneous in interests. In contrast the Evidence-Based clusters were well defined and largely homogeneous, so more useful for identifying functional relations with model outputs. The categorisations lead to two different clusterings of stakeholders and suggest unhelpful stereotyping of stakeholders may occur with the Intuitive categorisation method. Stakeholder clusters based on literature-evidence show a high degree of common interests among clusters and is encouraging for those seeking to maximise dialogue and consensus forming. © 2013 Elsevier Ltd.

Assessing family members' satisfaction with information sharing and communication during Hospital care at the end of life

Context: Despite the fact that most deaths occur in hospital, problems remain with how patients and families experience care at the end of life when a death occurs in a hospital. Objectives: (1) assess family member satisfaction with information sharing and communication, and (2) examine how satisfaction with information sharing and communication is associated with patient factors. Methods: Using a cross-sectional survey, data were collected from family members of adult patients who died in an acute care organization. Correlation and factor analysis were conducted, and internal consistency assessed using Cronbach's alpha. Linear regression was performed to determine the relationship among patient variables and satisfaction on the Information Sharing and Communication (ISC) scale. Results: There were 529 questionnaires available for analysis. Following correlation analysis and the dropping of redundant and conceptually irrelevant items, seven items remained for factor analysis. One factor was identified, described as information sharing and communication, that explained 76.3% of the variance. The questionnaire demonstrated good content and reliability (Cronbach's alpha 0.96). Overall, family members were satisfied with information sharing and communication (mean total satisfaction score 3.9, SD 1.1). The ISC total score was significantly associated with patient gender, the number of days in hospital before death, and the hospital program where the patient died. Conclusions: The ISC scale demonstrated good content validity and reliability. The ISC scale offers acute care organizations a means to assess the quality of information sharing and communication that transpires in care at the end of life. © Copyright 2013, Mary Ann Liebert, Inc.