Holistic design of 8-way combining transformers in SiGe technology for use in millimetre-wave power amplifiers

This paper presents the design of a novel 8-way power-combining transformer for use in mm-wave power amplifier (PA). The combiner exhibits a record low insertion loss of 1.25 dB at 83.5 GHz. A complete circuit comprised of a power splitter, two-stage cascode PA array, a power combiner and input/output matching elements was designed and realized in SiGe technology. Measured gain of at least 16.8 dB was obtained from 76.4 GHz to 85.3 GHz with a peak 19.5 dB at 83 GHz. The prototype delivered 12.5 dBm OP and 14 dBm saturated output power when operated from a 3.2 V DC supply voltage at 78 GHz. © 2013 IEEE.

Introduction to Domain-Driven Data Mining Special Section

In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.

New technology and new workplaces: call centre careers – a growing reality?

Research to date suggests that career advancement in call centres (CCs) is relatively uncommon with employees often viewing such employment as a stopgap measure before moving on to something better. This study set out to determine whether such scenarios have changed over time since CCs have become more established in their work organisation, information and communication technology (ICT) and management processes. This study particularly focused on training and development initiatives, how employees access training and development, and whether CCs support career development. Using both qualitative and quantitative methods, these issues are examined within 10 Australian CCs of varying size from various sectors. Two-thirds of respondents stated that they intended to develop a career in the industry and 7 in 10 reported that they believed there were promotional opportunities emerging in their current organisation. Despite these findings, the evidence also suggests that more needs to be done both to create coherent career paths and to establish structured, accredited training programmes for CC employees.

Towards a Mobile Assistive Technology for Monitoring and Assessing Cognitive Fatigue in Individuals with Acquired Brain Injury

Those living with an acquired brain injury often have issues with fatigue due to factors resulting from the injury. Cognitive impairments such as lack of memory, concentration and planning have a great impact on an individual’s ability to carry out general everyday tasks, which subsequently has the effect of inducing cognitive fatigue. Moreover, there is difficulty in assessing cognitive fatigue, as there are no real biological markers that can be measured. Rather, it is a very subjective effect that can only be diagnosed by the individual. Consequently, the traditional way of assessing cognitive fatigue is to use a self-assessment questionnaire that is able to determine contributing factors. State of the art methods to evaluate cognitive! fa tigue employ cognitive tests in order to analyse performance on predefined tasks. However, one primary issue with such tests is that they are typically carried out in a clinical environment, therefore do not have the ability to be utilized in situ within everyday life. This paper presents a smartphone application for the evaluation of fatigue, which can be used daily to track cognitive performance in order to assess the influence of fatigue.