Innovation dynamics and capability in open collaborative cyber communities: implications for cybersecurity

Cybersecurity is a complex challenge that has emerged alongside the evolving global socio-technical environment of social networks that feature connectivity across time and space in ways unimaginable even a decade ago. This paper reports on the preliminary findings of a NATO funded project that investigates the nature of innovation in open collaborative communities and its implications for cyber security. In this paper, the authors describe the framing of relevant issues, the articulation of the research questions, and the derivation of a conceptual framework based on open collaborative innovation that has emerged from preliminary field research in Russia and the UK.

Positive schizotypy and trait dissociation as vulnerability factors for post-traumatic distress

Objective. This study investigated whether trait positive schizotypy or trait dissociation was associated with increased levels of data-driven processing and symptoms of post-traumatic distress following a road traffic accident. Methods. Forty-five survivors of road traffic accidents were recruited from a London Accident and Emergency service. Each completed measures of trait positive schizotypy, trait dissociation, data-driven processing, and post-traumatic stress. Results. Trait positive schizotypy was associated with increased levels of data-driven processing and post-traumatic symptoms during a road traffic accident, whereas trait dissociation was not. Conclusions. Previous results which report a significant relationship between trait dissociation and post-traumatic symptoms may be an artefact of the relationship between trait positive schizotypy and trait dissociation.

A clocking technique for FPGA pipelined designs

This paper presents a clocking pipeline technique referred to as a single-pulse pipeline (PP-Pipeline) and applies it to the problem of mapping pipelined circuits to a Field Programmable Gate Array (FPGA). A PP-pipeline replicates the operation of asynchronous micropipelined control mechanisms using synchronous-orientated logic resources commonly found in FPGA devices. Consequently, circuits with an asynchronous-like pipeline operation can be efficiently synthesized using a synchronous design methodology. The technique can be extended to include data-completion circuitry to take advantage of variable data-completion processing time in synchronous pipelined designs. It is also shown that the PP-pipeline reduces the clock tree power consumption of pipelined circuits. These potential applications are demonstrated by post-synthesis simulation of FPGA circuits. (C) 2004 Elsevier B.V. All rights reserved.

An analysis on the performance of the forward and return interaction channels in DVB-RCS

The next generation consumer level interactive services require reliable and constant communication for both mobile and static users. The Digital Video Broadcasting ( DVB) group has exploited the rapidly increasing satellite technology for the provision of interactive services and launched a standard called Digital Video Broadcast through Return Channel Satellite (DYB-RCS). DVB-RCS relies on DVB-Satellite (DVB-S) for the provision of forward channel. The Digital Signal processing (DSP) implemented in the satellite channel adapter block of these standards use powerful channel coding and modulation techniques. The investigation is concentrated towards the Forward Error Correction (FEC) of the satellite channel adapter block, which will help in determining, how the technology copes with the varying channel conditions and user requirements(1).

An enhancement of the ionospheric sporadic‐E layer in response to negative polarity cloud‐to‐ground lightning

Lightning data, collected using a Boltek Storm Tracker system installed at Chilton, UK, were used to investigate the mean response of the ionospheric sporadic-E layer to lightning strokes in a superposed epoch study. The lightning detector can discriminate between positive and negative lightning strokes and between cloud-to-ground ( CG) and inter-cloud ( IC) lightning. Superposed epoch studies carried out separately using these subsets of lightning strokes as trigger events have revealed that the dominant cause of the observed ionospheric enhancement in the Es layer is negative cloud-to-ground lightning.

The application of affine projection to the development of a siren noise cancellation system

Emergency vehicles use high-amplitude sirens to warn pedestrians and other road users of their presence. Unfortunately, the siren noise enters the vehicle and corrupts the intelligibility of two-way radio voice com-munications from the emergency vehicle to a control room. Often the siren has to be turned off to enable the control room to hear what is being said which subsequently endangers people's lives. A digital signal processing (DSP) based system for the cancellation of siren noise embedded within speech is presented. The system has been tested with the least mean square (LMS), normalised least mean square (NLMS) and affine projection algorithm (APA) using recordings from three common types of sirens (two-tone, wail and yelp) from actual test vehicles. It was found that the APA with a projection order of 2 gives comparably improved cancellation over the LMS and NLMS with only a moderate increase in algorithm complexity and code size. Therefore, this siren noise cancellation system using the APA offers an improvement in cancellation achieved by previous systems. The removal of the siren noise improves the response time for the emergency vehicle and thus the system can contribute to saving lives. The system also allows voice communication to take place even when the siren is on and as such the vehicle offers less risk of danger when moving at high speeds in heavy traffic.

Normality mining: privacy implications of behavioral profiles drawn from GPS enabled mobile phones

There is growing interest in the ways in which the location of a person can be utilized by new applications and services. Recent advances in mobile technologies have meant that the technical capability to record and transmit location data for processing is appearing in off-the-shelf handsets. This opens possibilities to profile people based on the places they visit, people they associate with, or other aspects of their complex routines determined through persistent tracking. It is possible that services offering customized information based on the results of such behavioral profiling could become commonplace. However, it may not be immediately apparent to the user that a wealth of information about them, potentially unrelated to the service, can be revealed. Further issues occur if the user agreed, while subscribing to the service, for data to be passed to third parties where it may be used to their detriment. Here, we report in detail on a short case study tracking four people, in three European member states, persistently for six weeks using mobile handsets. The GPS locations of these people have been mined to reveal places of interest and to create simple profiles. The information drawn from the profiling activity ranges from intuitive through special cases to insightful. In this paper, these results and further extensions to the technology are considered in light of European legislation to assess the privacy implications of this emerging technology.

On the reprocessing and reanalysis of observations for climate

The long observational record is critical to our understanding of the Earth’s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide a climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Characterization of virus-like particles associated with the human faecal and caecal microbiota

This work represents an investigation into the presence, abundance and diversity of virus-like particles (VLPs) associated with human faecal and caecal samples. Various methodologies for the recovery of VLPs from faeces were tested and optimized, including successful down-stream processing of such samples for the purpose of an in-depth electron microscopic analysis, pulsed-field gel electrophoresis and efficient DNA recovery. The applicability of the developed VLP characterization method beyond the use of faecal samples was then verified using samples obtained from human caecal fluid.

Massive Open Online Courses and sustainability

Massive Open Online Courses (MOOCs) have become very popular among learners millions of users from around the world registered with leading platforms. There are hundreds of universities (and other organizations) offering MOOCs. However, sustainability of MOOCs is a pressing concern as MOOCs incur up front creation costs, maintenance costs to keep content relevant and on-going support costs to provide facilitation while a course is being run. At present, charging a fee for certification (for example Coursera Signature Track and FutureLearn Statement of Completion) seems a popular business model. In this paper, the authors discuss other possible business models and their pros and cons. Some business models discussed here are: Freemium model – providing content freely but charging for premium services such as course support, tutoring and proctored exams. Sponsorships – courses can be created in collaboration with industry where industry sponsorships are used to cover the costs of course production and offering. For example Teaching Computing course was offered by the University of East Anglia on the FutureLearn platform with the sponsorship from British Telecom while the UK Government sponsored the course Introduction to Cyber Security offered by the Open University on FutureLearn. Initiatives and Grants – The government, EU commission or corporations could commission the creation of courses through grants and initiatives according to the skills gap identified for the economy. For example, the UK Government’s National Cyber Security Programme has supported a course on Cyber Security. Similar initiatives could also provide funding to support relevant course development and offering. Donations – Free software, Wikipedia and early OER initiatives such as the MIT OpenCourseware accept donations from the public and this could well be used as a business model where learners could contribute (if they wish) to the maintenance and facilitation of a course. Merchandise – selling merchandise could also bring revenue to MOOCs. As many participants do not seek formal recognition (European Commission, 2014) for their completion of a MOOC, merchandise that presents their achievement in a playful way could well be attractive for them. Sale of supplementary material –supplementary course material in the form of an online or physical book or similar could be sold with the revenue being reinvested in the course delivery. Selective advertising – courses could have advertisements relevant to learners Data sharing – though a controversial topic, sharing learner data with relevant employers or similar could be another revenue model for MOOCs. Follow on events – the courses could lead to follow on summer schools, courses or other real-life or online events that are paid-for in which case a percentage of the revenue could be passed on to the MOOC for its upkeep. Though these models are all possible ways of generating revenue for MOOCs, some are more controversial and sensitive than others. Nevertheless unless appropriate business models are identified the sustainability of MOOCs would be problematic.

Storm track sensitivity to sea surface temperature resolution in a regional atmosphere model

A high resolution regional atmosphere model is used to investigate the sensitivity of the North Atlantic storm track to the spatial and temporal resolution of the sea surface temperature (SST) data used as a lower boundary condition. The model is run over an unusually large domain covering all of the North Atlantic and Europe, and is shown to produce a very good simulation of the observed storm track structure. The model is forced at the lateral boundaries with 15–20 years of data from the ERA-40 reanalysis, and at the lower boundary by SST data of differing resolution. The impacts of increasing spatial and temporal resolution are assessed separately, and in both cases increasing the resolution leads to subtle, but significant changes in the storm track. In some, but not all cases these changes act to reduce the small storm track biases seen in the model when it is forced with low-resolution SSTs. In addition there are several clear mesoscale responses to increased spatial SST resolution, with surface heat fluxes and convective precipitation increasing by 10–20% along the Gulf Stream SST gradient.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.