Detecting and monitoring of lymphoedema

Much of what we know about lymphoedema is derived from studies involving cancer cohorts, in particular breast cancer. Yet even within this setting, and despite the known profound physical, social and psychological effects, our understanding of associated risk factors and effectiveness of prevention and treatment strategies is poorly studied with inconsistent results. The limitations of our current methods to detect and monitor lymphoedema contribute to our lack of understanding of this condition. Current measurement approaches applied in the clinical and research setting will be described during this presentation. The strengths, limitations and practical considerations relevant to measurement methods will also be addressed. Improving the way we detect and monitor lymphoedema is necessary and critical for advancing the lymphoedema field and is relevant for the detection and monitoring of lymphoedema in the clinic as well as in research.

Managing ubiquitous eco cities : technology, infrastructure and management issues

Literature on Ubiquitous Eco Cities highlights three key issues to be carefully considered while planning, developing and managing such cities: ‘technology, infrastructure and management’. This paper discusses the recent developments in telecommunication networks, trends in technology convergence and both of their implications on the management of Ubiquitous Eco Cities. The paper also introduces recent approaches on urban management, such as intelligent urban management systems, that are potentially suitable for Ubiquitous Eco Cities.

Intelligent urban management systems : online decision support systems for ubiquitous cities

A successful urban management support system requires an integrated approach. This integration includes bringing together economic, socio-cultural and urban development with a well orchestrated, transparent and open decision making mechanism. The chapter emphasizes the importance of integrated urban management to better tackle the climate change, and to achieve sustainable urban development and sound urban growth management. This chapter introduces recent approaches on urban management systems, such as intelligent urban management systems, that are suitable for ubiquitous cities. The chapter discusses the essential role of online collaborative decision making in urban and infrastructure planning, development and management, and advocates transparent, fully democratic and participatory mechanisms for an effective urban management system that is particularly suitable for ubiquitous cities. This chapter also sheds light on some of the unclear processes of urban management of ubiquitous cities and online collaborative decision making, and reveals the key benefits of integrated and participatory mechanisms in successfully constructing sustainable ubiquitous cities.

Monitoring and regulating corporate identities using the balanced scorecard

Abstract: Purpose – The purpose of this paper is to provide a parallel review of the role and processes of monitoring and regulation of corporate identities, examining both the communication and the performance measurement literature. Design/methodology/approach – Two questions are posed: Is it possible to effectively monitor and regulate corporate identities as a management control process? and, What is the relationship between corporate identity and performance measurement? Findings – Corporate identity management is positioned as a strategically complex task embracing the shaping of a range of dimensions of organisational life. The performance measurement literature likewise now emphasises organisational ability to incorporate both financial and “soft” non-financial performance measures. Consequently, the balanced scorecard has the potential to play multiple roles in monitoring and regulating the key dimensions of corporate identities. These shifts in direction in both fields suggest that performance measurement systems, as self-producing and self-referencing systems, have the potential to become both organic and powerful as organisational symbols and communication tools. Through this process of understanding and mobilising the interaction of both approaches to management, it may be possible to create a less obtrusive and more subtle way to control the nature of the organisation. Originality/value – This paper attempts the theoretical and practical fusion of disciplinary knowledge around corporate identities and performance measurement systems, potentially making a significant contribution to understanding, shaping and managing organisational identities.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Structural health monitoring of bridges using acoustic emission technology

Bridges are an important part of society's infrastructure and reliable methods are necessary to monitor them and ensure their safety and efficiency. Bridges deteriorate with age and early detection of damage helps in prolonging the lives and prevent catastrophic failures. Most bridges still in used today were built decades ago and are now subjected to changes in load patterns, which can cause localized distress and if not corrected can result in bridge failure. In the past, monitoring of structures was usually done by means of visual inspection and tapping of the structures using a small hammer. Recent advancements of sensors and information technologies have resulted in new ways of monitoring the performance of structures. This paper briefly describes the current technologies used in bridge structures condition monitoring with its prime focus in the application of acoustic emission (AE) technology in the monitoring of bridge structures and its challenges.

Optimal monitoring in family-owned companies? Evidence from Asia

Manuscript Type: Empirical Research Issue: We propose that high levels of monitoring are not always in the best interests of minority shareholders. In family-owned companies the optimal level of board monitoring required by minority shareholders is expected to be lower than that of other companies. This is because the relative benefits and costs of monitoring are different in family-owned companies. Research Findings: At moderate levels of board monitoring, we find concave relationships between board monitoring variables and firm performance for family-owned companies but not for other companies. The optimal level of board monitoring for our sample of Asian family-owned companies equates to board independence of 38%, separation of the Chairman and CEO positions and establishment of audit and remuneration committees. Additional testing shows that the optimal level of board monitoring is sensitive to the magnitude of the agency conflict between the family group and minority shareholders and the presence of substitute monitoring. Practitioner/Policy Implications: For policymakers, the results show that more monitoring is not always in the best interests of minority shareholders. Therefore, it may be inappropriate for regulators to advise all companies to follow the same set of corporate governance guidelines. However, our results also indicate that the board governance practices of family-owned companies are still well below the identified optimal levels. Keywords: Corporate Governance, Board Independence, Board of Directors, Family Firms, Monitoring.

Polybrominated diphenyl ether (PBDE) concentrations decrease with age : analysis of pooled human blood serum in the Australian population

Introduction Polybrominated diphenyl ethers (PBDEs) are considered to be a cost effective and efficient way to reduce the possibility of product ignition and inhibit the spread of fire, thereby limiting harm caused by fires. PBDEs are incorporated into a wide variety of manufactured products and are now considered an ubiquitous contaminant found worldwide in biological and environmental samples . In comparison to “traditional” persistent organic pollutants (POPs), the exposure modes of PBDEs in humans are less well defined, although dietary sources, inhalation (air/particulate matter) and dust ingestion have been reported 2-4. Limited investigations of population specific factors such as age or gender and PBDE concentrations report: no conclusive correlation by age in adults ; higher concentrations in children ; similar concentrations in maternal and cord blood ; and no gender differences . After preliminary findings of higher PBDE concentrations in children than in adults in Australia11 we sought to investigate at what age the PBDE concentrations peaked in an effort to focus exposure studies. This investigation involved the collection of blood samples from young age groups and the development of a simple model to predict PBDE concentrations by age in Australia.

Apparatus for monitoring load bearing rehabilitation exercises of a transfemoral amputee fitted with an osseointegrated fixation : a proof-of-concept study

The purpose of this proof-of-concept study was to determine the relevance of direct measurements to monitor the load applied on the osseointegrated fixation of transfemoral amputees during static load bearing exercises. The objectives were (A) to introduce an apparatus using a three-dimensional load transducer, (B) to present a range of derived information relevant to clinicians, (C) to report on the outcomes of a pilot study and (D) to compare the measurements from the transducer with those from the current method using a weighing scale. One transfemoral amputee fitted with an osseointegrated implant was asked to apply 10 kg, 20 kg, 40 kg and 80 kg on the fixation, using self-monitoring with the weighing scale. The loading was directly measured with a portable kinetic system including a six-channel transducer, external interface circuitry and a laptop. As the load prescribed increased from 10 kg to 80 kg, the forces and moments applied on and around the antero-posterior axis increased by 4 fold anteriorly and 14 fold medially, respectively. The forces and moments applied on and around the medio-lateral axis increased by 9 fold laterally and 16 fold from anterior to posterior, respectively. The long axis of the fixation was overloaded and underloaded in 17 % and 83 % of the trials, respectively, by up to ±10 %. This proof-of-concept study presents an apparatus that can be used by clinicians facing the challenge of improving basic knowledge on osseointegration, for the design of equipment for load bearing exercises and for rehabilitation programs.

Rover autonomous integrity monitoring of GNSS RTK positioning solutions with multi-constellations

This paper studies receiver autonomous integrity monitoring (RAIM) algorithms and performance benefits of RTK solutions with multiple-constellations. The proposed method is generally known as Multi-constellation RAIM -McRAIM. The McRAIM algorithms take advantage of the ambiguity invariant character to assist fast identification of multiple satellite faults in the context of multiple constellations, and then detect faulty satellites in the follow-up ambiguity search and position estimation processes. The concept of Virtual Galileo Constellation (VGC) is used to generate useful data sets of dual-constellations for performance analysis. Experimental results from a 24-h data set demonstrate that with GPS&VGC constellations, McRAIM can significantly enhance the detection and exclusion probabilities of two simultaneous faulty satellites in RTK solutions.