A new distributed control strategy to coordinate multiple dstatcoms in LV network

Voltage rise is the main issue which limits the capacity of Low Voltage (LV) network to accommodate more Renewable Energy (RE) sources. In addition, voltage drop at peak load period is a significant power quality concern. This paper proposes a new robust voltage support strategy based on distributed coordination of multiple distribution static synchronous compensators (DSTATCOMs). The study focuses on LV networks with PV as the RE source for customers. The proposed approach applied to a typical LV network and its advantages are shown comparing with other voltage control strategies.

Undulating matter : a topology of the studio

With specific reference to the writing of Dan Graham and the experiences of creative practice, this paper will elaborate an account of studio practice as a topology - a theory drawn from mathematics in which space is understood not as a static field but in terms of properties of connectedness, movement and differentiation. This paper will trace a brief sequence of topological formulations to draw together the expression of topology as form and its structural dimension as a methodology in the specific context of the author’s studio practice. In so doing, this paper seeks to expand the notion of topology in art beyond its association with Conceptual Art of the 1960s and 70s to propose that topology provides a dynamic theoretical model for apprehending the generative ‘logic’ that gives direction and continuity to the art-making process.

Inpatient facial expression recognition with SMS alert

Facial expression recognition (FER) has been dramatically developed in recent years, thanks to the advancements in related fields, especially machine learning, image processing and human recognition. Accordingly, the impact and potential usage of automatic FER have been growing in a wide range of applications, including human-computer interaction, robot control and driver state surveillance. However, to date, robust recognition of facial expressions from images and videos is still a challenging task due to the difficulty in accurately extracting the useful emotional features. These features are often represented in different forms, such as static, dynamic, point-based geometric or region-based appearance. Facial movement features, which include feature position and shape changes, are generally caused by the movements of facial elements and muscles during the course of emotional expression. The facial elements, especially key elements, will constantly change their positions when subjects are expressing emotions. As a consequence, the same feature in different images usually has different positions. In some cases, the shape of the feature may also be distorted due to the subtle facial muscle movements. Therefore, for any feature representing a certain emotion, the geometric-based position and appearance-based shape normally changes from one image to another image in image databases, as well as in videos. This kind of movement features represents a rich pool of both static and dynamic characteristics of expressions, which playa critical role for FER. The vast majority of the past work on FER does not take the dynamics of facial expressions into account. Some efforts have been made on capturing and utilizing facial movement features, and almost all of them are static based. These efforts try to adopt either geometric features of the tracked facial points, or appearance difference between holistic facial regions in consequent frames or texture and motion changes in loca- facial regions. Although achieved promising results, these approaches often require accurate location and tracking of facial points, which remains problematic.

Vertical displacement measurement using fibre Bragg grating (FBG) sensors for structural health monitoring of bridges

This thesis developed a practical, cost effective, easy-to-use method for measuring the vertical displacements of bridges using fiber Bragg grating (FBG) sensors, which includes the curvature and inclination approaches. These approaches were validated by the numerical simulation tests on a full scale bridge and the laboratory-based tests. In doing so, a novel frictionless FBG inclination sensor with extremely high sensitivity and resolution has also been developed and validated.

Cheating prevention in secret sharing over GF(pt)

The work investigates cheating prevention in secret sharing. It is argued that cheating is immune against cheating if the cheaters gain no advantage over honest participants by submitting invalid shares to the combiner. This work addresses the case when shares and the secret are taken from GF(pt). Two models are considered. The first one examines the case when cheaters consistently submit always invalid shares. The second modeldeal s with cheaters who submit a mixture of valid and invalid shares. For these two models, cheating immunity is defined, properties of cheating immune secret sharing are investigated and their constructions are given.

The -Omics in drug development

New advancement in genomics, proteomics, and metabonomics created significant excitement about the use of these relatively new technologies in drug design, discovery, development, and molecular-targeted therapeutics by identifying new drug targets and better tools for safety and efficacy studies in preclinical and clinical stages of drug development as well as diagnostics. In this chapter, we will briefly discuss the application of genomics, proteomics, and metabonomics in drug discovery and development

High-rate, low-temperature synthesis of composition controlled hydrogenated amorphous silicon carbide films in low-frequency inductively coupled plasmas

It is commonly believed that in order to synthesize high-quality hydrogenated amorphous silicon carbide (a-Si1-xCx : H) films at competitive deposition rates it is necessary to operate plasma discharges at high power regimes and with heavy hydrogen dilution. Here we report on the fabrication of hydrogenated amorphous silicon carbide films with different carbon contents x (ranging from 0.09 to 0.71) at high deposition rates using inductively coupled plasma (ICP) chemical vapour deposition with no hydrogen dilution and at relatively low power densities (∼0.025 W cm -3) as compared with existing reports. The film growth rate R d peaks at x = 0.09 and x = 0.71, and equals 18 nm min-1 and 17 nm min-1, respectively, which is higher than other existing reports on the fabrication of a-Si1-xCx : H films. The extra carbon atoms for carbon-rich a-Si1-xCx : H samples are incorporated via diamond-like sp3 C-C bonding as deduced by Fourier transform infrared absorption and Raman spectroscopy analyses. The specimens feature a large optical band gap, with the maximum of 3.74 eV obtained at x = 0.71. All the a-Si1-xCx : H samples exhibit low-temperature (77 K) photoluminescence (PL), whereas only the carbon-rich a-Si1-xCx : H samples (x ≥ 0.55) exhibit room-temperature (300 K) PL. Such behaviour is explained by the static disorder model. High film quality in our work can be attributed to the high efficiency of the custom-designed ICP reactor to create reactive radical species required for the film growth. This technique can be used for a broader range of material systems where precise compositional control is required. © 2008 IOP Publishing Ltd.

Self-action of high-frequency surface waves in a magnetoactive planar plasma waveguide

The self-modulation process of a high-frequency surface wave (SW) in a wave-guiding structure - a semibounded magnetoactive plasma and perfectly conducting metal wall - is considered for the weak nonlinearity approximation. Estimates are given for the contributions to the nonlinear frequency shift of the SW from the two principal self-action channels: via the generation of a signal of the doubled frequency and of static surface perturbations, arising as the result of the action of a ponderomotive force. Solutions for the field envelope of the nonlinear wave are examined with regard to their stability with respect to longitudinal and transverse perturbations.

Nonlinear electromagnetic fields in 0.5 MHz inductively coupled plasmas

Radial profiles of magnetic fields in the electrostatic (E) and electromagnetic (H) modes of low-frequency (∼500) inductively coupled plasmas (ICP) were measured using miniature magnetic probes. A simplified plasma fluid model explaining the generation of the second harmonics of the azimuthal magnetic field in the plasma source was proposed. Because of apparent similarity in the procedure of derivation of the pondermotive force-caused nonlinear terms, pronounced generation of the nonlinear static azimuthal magnetic field could be expected.

Self-interaction of high-frequency surface waves in magnetoactive plasma planar waveguide

The nonlinear effect of hf surface waves self-interaction in a magnetoactive planar plasma waveguide is studies. The waveguide structure under consideration can be formed by gaseous or semiconducting homogeneous plasma, which is limited by a perfectly conducting metal surface. The surface (localized near the surface) wave perturbations propagating on the plasma-metal boundary perpendicular to the constant external magnetic field, are investigated. The nonlinear frequency shift connected with interaction of the second harmonic and static surface perturbations with the main frequency wave, is determined using the approximation of weak nonlinearity. It is shown that the process of double-frequency signal generation is the dissipative one as a result of bulk wave excitation on the surface wave second harmonic.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

Seat Comfort. M2-M3

This (seat) attribute target list and Design for Comfort taxonomy report is based on the literature review report (C3-21, Milestone 1), which specified different areas (factors) with specific influence on automotive seat comfort. The attribute target list summarizes seat factors established in the literature review (Figure 1) and subsumes detailed attributes derived from the literature findings within these factors/classes. The attribute target list (Milestone 2) then provides the basis for the “Design for Comfort” taxonomy (Milestone 3) and helps the project develop target settings (values) that will be measured during the testing phase of the C3-21 project. The attribute target list will become the core technical description of seat attributes, to be incorporated into the final comfort procedure that will be developed. The Attribute Target List and Design for Comfort Taxonomy complete the target definition process. They specify the context, markets and application (vehicle classes) for seat development. As multiple markets are addressed, the target setting requires flexibility of variables to accommodate the selected customer range. These ranges will be consecutively filled with data in forthcoming studies. The taxonomy includes how and where the targets are derived, reference points and standards, engineering and subjective data from previous studies as well as literature findings. The comfort parameters are ranked to identify which targets, variables or metrics have the biggest influence on comfort. Comfort areas included are seat kinematics (adjustability), seat geometry and pressure distribution (static comfort), seat thermal behavior and noise/vibration transmissibility (cruise comfort) and eventually material properties, design and features (seat harmony). Data from previous studies is fine tuned and will be validated in the nominated contexts and markets in follow-up dedicated studies.

Impact forces at dipped rail joints

Impact forces develop at the wheel/rail interface due to the presence of defects in the running surface of the wheel and/ or the railhead. This paper reports on wheel impacts, caused by permanently dipped rail joints, that are characterised by high-frequency impact forces generated by high amplifications of the static load that occur for a very short duration (P1 forces), followed by relatively low frequency, lower amplitude forces (P2 forces) that occur for a longer duration. These impact forces are affected by the design of components adjacent to the wheel and rail, namely the bogie’s primary suspension and rail seat pads; the influences of stiffness and damping characteristics of these components are investigated. A modified three-dimensional simulation model of the dynamics of the wagon/track system that includes defects in the track is created and is used to obtain the time series of the impact force. This is converted into impact force factors that are compared with a set of field-measured data reported in the literature. A simplified equation for the determination of impact force factors due to dipped rail joints is also proposed and validated.

Simultaneous localization and planning on multiple map hypotheses

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.