Experimental full duplex simultaneous transmission of LTE over a DWDM directly modulated RoF system

In this paper, we experimentally demonstrate the seamless integration of full duplex system frequency division duplex (FDD) long-term evolution (LTE) technology with radio over fiber (RoF) for eNodeB (eNB) coverage extension. LTE is composed of quadrature phase-shift keying (QPSK), 16-quadrature amplitude modulation (16-QAM) and 64-QAM, modulated onto orthogonal frequency division multiplexing (OFDM) and single-carrier-frequency division multiplexing for downlink (DL) and uplink (UL) transmissions, respectively. The RoF system is composed of dedicated directly modulated lasers for DL and UL with dense wavelength division multiplexing (DWDM) for instantaneous connections and for Rayleigh backscattering and nonlinear interference mitigation. DL and UL signals have varying carrier frequencies and are categorized as broad frequency spacing (BFS), intermediate frequency spacing (IFS), and narrow frequency spacing (NFS). The adjacent channel leakage ratio (ACLR) for DL and UL with 64-QAM are similar for all frequency spacings while cross talk is observed for NFS. For the best case scenario for DL and UL transmissions we achieve error vector magnitude (EVM) values of ~2.30%, ~2.33%, and ~2.39% for QPSK, 16-QAM, and 64-QAM, respectively, while for the worst case scenario with a NFS EVM is increased by 0.40% for all schemes. © 2009-2012 OSA.

Radio range adjustment for energy efficient wireless sensor networks

In wireless ad hoc sensor networks, energy use is in many cases the most important constraint since it corresponds directly to operational lifetime. Topology management schemes such as GAF put the redundant nodes for routing to sleep in order to save the energy. The radio range will affect the number of neighbouring nodes, which collaborate to forward data to a base station or sink. In this paper we study a simple linear network and deduce the relationship between optimal radio range and traffic. We find that half of the power can be saved if the radio range is adjusted appropriately compared with the best case where equal radio ranges are used.

Inspiring lecturers: sharing e-learning practice through european case studies

What motivates a university lecturer to consider introducing a new e-learning approach to their educational practice? Accounts of e-learning practice can invite discussion and reflection on the approaches taken, reinforcement of a particular model, connection with the experience of others, vicarious learning opportunities and glimpses into tacit knowledge. If these examples provoke thinking, could they have the ‘sticky qualities’, the memorable inspiration and ideas that move us to action, when we observe the practice of others? (Szulanski, 2003) “Case studies have the capacity to inspire but also to provoke and to challenge.” (JISC, 2004) This paper will discuss a process followed for sharing best practices of e-learning. It will explain how good practices were identified and gathered by the EUNIS E-Learning Task Force collaboration, using a database and a weblog (EUNIC, 2008). It will examine the methods used for the developing and compiling of the practices and the communication of these. Actual examples of some of the case studies gathered will be included in an appendix. Suggestions of ways to develop this process further and the tangible benefits identified will be examined to ask if effective practice can also become embedded practice.

The brain in business:the case for organizational cognitive neuroscience?

The application of cognitive neuroscientific techniques to understanding social behaviour has resulted in many discoveries. Yet advocates of the ‘social cognitive neuroscience’ approach maintain that it suffers from a number of limitations. The most notable of these is its distance from any form of real-world applicabity. One solution to this limitation is ‘Organisational Cognitive Neuroscience’ – the study of the cognitive neuroscience of human behaviour in, and in response to, organizations. Given that all of us will spend most of our lives in some sort of work related organisation, organisational cognitive neuroscience allows us to examine the cognitive underpinnings of social behaviour that occurs in what may be our most natural ecology. Here we provide a brief overview of this approach, a definition and also some possible questions that the new approach would be best suited to address.

Lexical and nonlexical processing in developmental dyslexia: a case for different resources and different impairments

In a group of adult dyslexics word reading and, especially, word spelling are predicted more by what we have called lexical learning (tapped by a paired-associate task with pictures and written nonwords) than by phonological skills. Nonword reading and spelling, instead, are not associated with this task but they are predicted by phonological tasks. Consistently, surface and phonological dyslexics show opposite profiles on lexical learning and phonological tasks. The phonological dyslexics are more impaired on the phonological tasks, while the surface dyslexics are equally or more impaired on the lexical learning tasks. Finally, orthographic lexical learning explains more variation in spelling than in reading, and subtyping based on spelling returns more interpretable results than that based on reading. These results suggest that the quality of lexical representations is crucial to adult literacy skills. This is best measured by spelling and best predicted by a task of lexical learning. We hypothesize that lexical learning taps a uniquely human capacity to form new representations by recombining the units of a restricted set.

Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

Scenario planning:teaching how to anticipate perceived environmental uncertainty within strategy development

Scenario Planning is a strategy tool with growing popularity in both academia and practical situations. Current practices in the teaching of scenario planning are largely based on existing literature which utilises scenario planning to develop strategies for the future, primarily considering the assessment of perceived macro-external environmental uncertainties. However there is a body of literature hitherto ignored by scenario planning researchers, which suggests that Perceived Environmental Uncertainty (PEU) influences micro-external or industrial environmental as well as the internal environment of the organisation. This paper provides a review of the most dominant theories on scenario planning process, demonstrates the need to consider PEU theory within scenario planning and presents how this can be done. The scope of this paper is to enhance the scenario planning process as a tool taught for Strategy Development. A case vignette is developed based on published scenarios to demonstrate the potential utilisation of the proposed process.

The advanced learner variety:the case of French

This volume originates from a workshop entitled 'Revisiting advanced varieties in L2 learning' organized by the editors at Aston University (Birmingham, UK) in June 2006. It consists of a peer-reviewed selection of the best contributions. Many different approaches have been used in the study of advanced learners and their characteristics. Specific areas of language have repeatedly been found to remain problematic even at advanced levels, and much empirical research has been carried out. In particular, areas of grammar such as the tense or agreement systems often pose difficulties, as well as lexical idiosyncrasies such as formulaic sequences, and the discourse/pragmatic constraints operating in French. This volume brings together recent research exploring the advanced learner capabilities in each of those domains, as well as possible explanations for the difficulties they raise for the L2 learner of French. Additionally, one of the areas which has received considerable attention in the French L2 literature on advanced learners, tense and aspect, is also explored from the point of view of French learners of English, to explore any parallels. In presenting this research, the book clarifies the concept of the advanced learner: how does s/he differ from native speakers and why?

Testing incremental politics : the case of North Sea oil

In the quest to secure the much vaunted benefits of North Sea oil, highly non-incremental technologies have been adopted. Nowhere is this more the case than with the early fields of the central and northern North Sea. By focusing on the inflexible nature of North Sea hardware, in such fields, this thesis examines the problems that this sort of technology might pose for policy making. More particularly, the following issues are raised. First, the implications of non-incremental technical change for the successful conduct of oil policy is raised. Here, the focus is on the micro-economic performance of the first generation of North Sea oil fields and the manner in which this relates to government policy. Secondly, the question is posed as to whether there were more flexible, perhaps more incremental policy alternatives open to the decision makers. Conclusions drawn relate to the degree to which non-incremental shifts in policy permit decision makers to achieve their objectives at relatively low cost. To discover cases where non-incremental policy making has led to success in this way, would be to falsify the thesis that decision makers are best served by employing incremental politics as an approach to complex problem solving.

Statnote 25: Stepwise multiple regression

An investigator may also wish to select a small subset of the X variables which give the best prediction of the Y variable. In this case, the question is how many variables should the regression equation include? One method would be to calculate the regression of Y on every subset of the X variables and choose the subset that gives the smallest mean square deviation from the regression. Most investigators, however, prefer to use a ‘stepwise multiple regression’ procedure. There are two forms of this analysis called the ‘step-up’ (or ‘forward’) method and the ‘step-down’ (or ‘backward’) method. This Statnote illustrates the use of stepwise multiple regression with reference to the scenario introduced in Statnote 24, viz., the influence of climatic variables on the growth of the crustose lichen Rhizocarpon geographicum (L.)DC.

Which is the best solar thermal collection technology for electricity generation in north-west India? Evaluation of options using the analytical hierarchy process

This study of concentrating solar thermal power generation sets out to evaluate the main existing collection technologies using the framework of the Analytical Hierarchy Process (AHP). It encompasses parabolic troughs, heliostat fields, linear Fresnel reflectors, parabolic dishes, compound parabolic concentrators and linear Fresnel lenses. These technologies are compared based on technical, economic and environmental criteria. Within these three categories, numerous sub-criteria are identified; similarly sub-alternatives are considered for each technology. A literature review, thermodynamic calculations and an expert workshop have been used to arrive at quantitative and qualitative assessments. The methodology is applied principally to a case study in Gujarat in north-west India, though case studies based on the Sahara Desert, Southern Spain and California are included for comparison. A sensitivity analysis is carried out for Gujarat. The study concludes that the linear Fresnel lens with a secondary compound parabolic collector, or the parabolic dish reflector, is the preferred technology for north-west India.

Scenario planning at business unit level

The scenario planning literature is focused on corporate level interventions. There is a general consensus on the method, but there is little debate about the stages involved in building and using the scenarios. This article presents a case study of a scenario planning intervention, which was conducted at a business unit of the British division of one of the largest beauty and cosmetic products multinationals. The method adopted in this case study has some fundamental differences to the existing models used at corporate level. This research is based on the principles of autoethnography, since its purpose is to present self-critical reflections, enhanced by reflective and reflexive conversations on a scenario planning method used at business unit level. The critical reflections concern a series of critical incidents which distinguish this method from existing intuitive logic scenario planning models which are used at corporate level planning. Ultimately this article contributes to the scenario planning method literature by providing insights into its practice at business unit level. © 2012 Elsevier Ltd.

The experience of delivering case award research in a public sector setting

The CASE Award PhD is a relatively new approach to completing academic research degrees, aligning the ideals of comprehensive research training and cross-collaboration between academics and organisations. As the initial wave of CASE funded PhD research begins to near completion, and indeed become evident through the publication of results, now is an appropriate time to begin the evaluation process of how to successfully deliver a CASE PhD, and to analyse the best practice approaches of completing a CASE Award with an organisation. This article intends to offer a picture into the CASE PhD process, with a focus on methods of communication to successfully implement this kind of research in collaboration with an organisation.

Dynamic decision networks for decision-making in self-adaptive systems:a case study

Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and speci?cally in the area of self-adaptive systems (SASs), little progress has been made in the application of Bayesian decision theory. We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. In this paper, we discuss the case for the use of BNs, speci?cally Dynamic Decision Networks (DDNs), to support the decision-making of self-adaptive systems. We present how such a probabilistic model can be used to support the decision making in SASs and justify its applicability. We have applied our DDN-based approach to the case of an adaptive remote data mirroring system. We discuss results, implications and potential bene?ts of the DDN to enhance the development and operation of self-adaptive systems, by providing mechanisms to cope with uncertainty and automatically make the best decision.

Case study as a research strategy : investigating extreme weather resilience of construction SMEs in the UK

Determining an appropriate research methodology is considered as an important element in a research study; especially in a doctoral research study. It involves approach to the entire process of a research study, starting from theoretical underpinnings and spanning to data collection and analysis, and extending to developing the solutions for the problems investigated. Research methodology in essence is focused around the problems to be investigated in a research study and therefore varies according to the problems investigated. Thus, identifying the research methodology that best suits a research in hand is important, not only as it will benefit achieving the set objectives of a research, but also as it will serve establishing the credibility of the work. Research philosophy, approach, strategy, choice, and techniques are inherent components of the methodology. Research strategy provides the overall direction of the research including the process by which the research is conducted. Case study, experiment, survey, action research, grounded theory and ethnography are examples for such research strategies. Case study is documented as an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident. Case study was adopted as the overarching research strategy, in a doctoral study developed to investigate the resilience of construction Small and Medium-sized Enterprises (SMEs) in the UK to extreme weather events. The research sought to investigate how construction SMEs are affected by EWEs, respond to the risk of EWEs, and means of enhancing their resilience to future EWEs. It is argued that utilising case study strategy will benefit the research study, in achieving the set objectives of the research and answering the research questions raised, by comparing and contrasting with the alternative strategies available. It is also claimed that the selected strategy will contribute towards addressing the call for improved methodological pluralism in construction management research, enhancing the understanding of complex network of relationships pertinent to the industry and the phenomenon being studied.