Mobile Wearable Communications

This special issue provides the latest research and development on wireless mobile wearable communications. According to a report by Juniper Research, the market value of connected wearable devices is expected to reach $1.5 billion by 2014, and the shipment of wearable devices may reach 70 million by 2017. Good examples of wearable devices are the prominent Google Glass and Microsoft HoloLens. As wearable technology is rapidly penetrating our daily life, mobile wearable communication is becoming a new communication paradigm. Mobile wearable device communications create new challenges compared to ordinary sensor networks and short-range communication. In mobile wearable communications, devices communicate with each other in a peer-to-peer fashion or client-server fashion and also communicate with aggregation points (e.g., smartphones, tablets, and gateway nodes). Wearable devices are expected to integrate multiple radio technologies for various applications' needs with small power consumption and low transmission delays. These devices can hence collect, interpret, transmit, and exchange data among supporting components, other wearable devices, and the Internet. Such data are not limited to people's personal biomedical information but also include human-centric social and contextual data. The success of mobile wearable technology depends on communication and networking architectures that support efficient and secure end-to-end information flows. A key design consideration of future wearable devices is the ability to ubiquitously connect to smartphones or the Internet with very low energy consumption. Radio propagation and, accordingly, channel models are also different from those in other existing wireless technologies. A huge number of connected wearable devices require novel big data processing algorithms, efficient storage solutions, cloud-assisted infrastructures, and spectrum-efficient communications technologies.

Increasing Staff and Student Capacity to Use the Communication Facility in Queen's Online in Order to Support Learning and Teaching on a BSW Programme

In this article the authors explore and evaluate developments in the use of information and communications technologies (ICT) within social work education at Queen's University Belfast since the inception of the new degree in social work. They look at the staff development strategy utilised to increase teacher confidence and competence in use of the Queen's Online virtual learning environment tools as well as the student experience of participation in modules involving online discussions. The authors conclude that the project provided further opportunity to reflect on how ICT can be used as a platform to support a whole course in a systematic and coordinated way and to ensure all staff remained abreast of ongoing developments in the use of ICT to support learning which is a normative expectation of students entering universities. A very satisfying outcome for the leaders is our observation of the emergence of other 'experts' in different aspects of use of ICT amongst the staff team. This project also shows that taking a team as opposed to an individual approach can be particularly beneficial

Intrusion Detection System for Network Security in Synchrophasor Systems

Synchrophasor systems will play a crucial role in next generation Smart Grid monitoring, protection and control. However these systems also introduce a multitude of potential vulnerabilities from malicious and inadvertent attacks, which may render erroneous operation or severe damage. This paper proposes a Synchrophasor Specific Intrusion Detection System (SSIDS) for malicious cyber attack and unintended misuse. The SSIDS comprises a heterogeneous whitelist and behavior-based approach to detect known attack types and unknown and so-called ‘zero-day’ vulnerabilities and attacks. The paper describes reconnaissance, Man-in-the-Middle (MITM) and Denial-of-Service (DoS) attack types executed against a practical synchrophasor system which are used to validate the real-time effectiveness of the proposed SSIDS cyber detection method.

ASIP: developments, challenges and trends

Application Specific Instruction Set Processor (ASIP) becomes an attractive substitute for ASIC as transistor density, logic complexity and market competition boost. Similar to ASIC, ASIP is based on customized and tailored architectures. In this way, ASIP delivers high performances with low overheads on cost and power whilst taking the advantages of high flexibility and fast time-to-market as a processor-based solution. To demonstrate this effective solution for embedded applications, this paper performs an overall investigation on ASIP's developments, challenges, trends in terms of architectures and design methodologies.

Towards Multi-Sensor Spectral Alignment Through Post Measurement Calibration Correction

Semiconductor manufactures are increasing reliant on optical emission spectroscopy (OES) to source information on plasma characteristics and process change. However, nonlinearities in the response of OES sensors and errors in their calibration lead to discrepancies in observed wavelength detector response. This paper presents a technique for the retrospective spectral calibration of multiple OES sensors. Underlying methodology is given, and alignment performance is evaluated using OES recordings from a semiconductor plasma process. The paper concludes with a discussion of results and suggests avenues for future work.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Managing Future offshore wind power variability in a European Supergrid

The future European power system will have a hierarchical structure created by layers of system control from a Supergrid via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the context of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called 'back-up generation' needed to support an 80% renewable energy portfolio in Europe by 2050. © 2013 IEEE.

Managing the variability of supply in the European power system with high wind energy penetration

The power system of the future will have a hierarchical structure created by layers of system control from via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the concept of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called ‘back-up generation’ needed to support an 80% renewable energy portfolio in Europe by 2050.

Internet of Things. A proposed secured network topology

The myriad of technologies and protocols working at different layers pose significant security challenges in the upcoming Internet of Things (IoT) paradigm. Security features and needs vary from application to application and it is layer specific. In addition, security has to consider the constraints imposed by energy limited sensor nodes and consider the specific target application in order to provide security at different layers. This paper analyses current standardization efforts and protocols. It proposes a generic secured network topology for IoT and describes the relevant security challenges. Some exploitation examples are also provided.